{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Requirement already satisfied: tensorflow in c:\\users\\fer_u\\pycharmprojects\\cyberattacksattention\\venv\\lib\\site-packages (2.11.0)\n",
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      "Requirement already satisfied: pyasn1-modules>=0.2.1 in c:\\users\\fer_u\\pycharmprojects\\cyberattacksattention\\venv\\lib\\site-packages (from google-auth<3,>=1.6.3->tensorboard<2.12,>=2.11->tensorflow-intel==2.11.0->tensorflow) (0.2.8)\n",
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      "Requirement already satisfied: requests-oauthlib>=0.7.0 in c:\\users\\fer_u\\pycharmprojects\\cyberattacksattention\\venv\\lib\\site-packages (from google-auth-oauthlib<0.5,>=0.4.1->tensorboard<2.12,>=2.11->tensorflow-intel==2.11.0->tensorflow) (1.3.1)\n",
      "Requirement already satisfied: importlib-metadata>=4.4 in c:\\users\\fer_u\\pycharmprojects\\cyberattacksattention\\venv\\lib\\site-packages (from markdown>=2.6.8->tensorboard<2.12,>=2.11->tensorflow-intel==2.11.0->tensorflow) (5.1.0)\n",
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      "Requirement already satisfied: certifi>=2017.4.17 in c:\\users\\fer_u\\pycharmprojects\\cyberattacksattention\\venv\\lib\\site-packages (from requests<3,>=2.21.0->tensorboard<2.12,>=2.11->tensorflow-intel==2.11.0->tensorflow) (2022.12.7)\n",
      "Requirement already satisfied: MarkupSafe>=2.1.1 in c:\\users\\fer_u\\pycharmprojects\\cyberattacksattention\\venv\\lib\\site-packages (from werkzeug>=1.0.1->tensorboard<2.12,>=2.11->tensorflow-intel==2.11.0->tensorflow) (2.1.1)\n",
      "Requirement already satisfied: zipp>=0.5 in c:\\users\\fer_u\\pycharmprojects\\cyberattacksattention\\venv\\lib\\site-packages (from importlib-metadata>=4.4->markdown>=2.6.8->tensorboard<2.12,>=2.11->tensorflow-intel==2.11.0->tensorflow) (3.11.0)\n",
      "Requirement already satisfied: pyasn1<0.5.0,>=0.4.6 in c:\\users\\fer_u\\pycharmprojects\\cyberattacksattention\\venv\\lib\\site-packages (from pyasn1-modules>=0.2.1->google-auth<3,>=1.6.3->tensorboard<2.12,>=2.11->tensorflow-intel==2.11.0->tensorflow) (0.4.8)\n",
      "Requirement already satisfied: oauthlib>=3.0.0 in c:\\users\\fer_u\\pycharmprojects\\cyberattacksattention\\venv\\lib\\site-packages (from requests-oauthlib>=0.7.0->google-auth-oauthlib<0.5,>=0.4.1->tensorboard<2.12,>=2.11->tensorflow-intel==2.11.0->tensorflow) (3.2.2)\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "WARNING: You are using pip version 21.3.1; however, version 22.3.1 is available.\n",
      "You should consider upgrading via the 'C:\\Users\\Fer_U\\PycharmProjects\\CyberattacksAttention\\venv\\Scripts\\python.exe -m pip install --upgrade pip' command.\n"
     ]
    }
   ],
   "source": [
    "!pip install tensorflow"
   ],
   "metadata": {
    "collapsed": false,
    "pycharm": {
     "name": "#%%\n"
    }
   }
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Requirement already satisfied: pandas in c:\\users\\fer_u\\pycharmprojects\\cyberattacksattention\\venv\\lib\\site-packages (1.5.2)\n",
      "Requirement already satisfied: numpy>=1.20.3 in c:\\users\\fer_u\\pycharmprojects\\cyberattacksattention\\venv\\lib\\site-packages (from pandas) (1.23.5)\n",
      "Requirement already satisfied: python-dateutil>=2.8.1 in c:\\users\\fer_u\\pycharmprojects\\cyberattacksattention\\venv\\lib\\site-packages (from pandas) (2.8.2)\n",
      "Requirement already satisfied: pytz>=2020.1 in c:\\users\\fer_u\\pycharmprojects\\cyberattacksattention\\venv\\lib\\site-packages (from pandas) (2022.6)\n",
      "Requirement already satisfied: six>=1.5 in c:\\users\\fer_u\\pycharmprojects\\cyberattacksattention\\venv\\lib\\site-packages (from python-dateutil>=2.8.1->pandas) (1.16.0)\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "WARNING: You are using pip version 21.3.1; however, version 22.3.1 is available.\n",
      "You should consider upgrading via the 'C:\\Users\\Fer_U\\PycharmProjects\\CyberattacksAttention\\venv\\Scripts\\python.exe -m pip install --upgrade pip' command.\n"
     ]
    }
   ],
   "source": [
    "!pip install pandas"
   ],
   "metadata": {
    "collapsed": false,
    "pycharm": {
     "name": "#%%\n"
    }
   }
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Requirement already satisfied: neural_structured_learning in c:\\users\\fer_u\\pycharmprojects\\cyberattacksattention\\venv\\lib\\site-packages (1.4.0)\n",
      "Requirement already satisfied: absl-py in c:\\users\\fer_u\\pycharmprojects\\cyberattacksattention\\venv\\lib\\site-packages (from neural_structured_learning) (1.3.0)\n",
      "Requirement already satisfied: scipy in c:\\users\\fer_u\\pycharmprojects\\cyberattacksattention\\venv\\lib\\site-packages (from neural_structured_learning) (1.9.3)\n",
      "Requirement already satisfied: attrs in c:\\users\\fer_u\\pycharmprojects\\cyberattacksattention\\venv\\lib\\site-packages (from neural_structured_learning) (22.1.0)\n",
      "Requirement already satisfied: six in c:\\users\\fer_u\\pycharmprojects\\cyberattacksattention\\venv\\lib\\site-packages (from neural_structured_learning) (1.16.0)\n",
      "Requirement already satisfied: numpy<1.26.0,>=1.18.5 in c:\\users\\fer_u\\pycharmprojects\\cyberattacksattention\\venv\\lib\\site-packages (from scipy->neural_structured_learning) (1.23.5)\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "WARNING: You are using pip version 21.3.1; however, version 22.3.1 is available.\n",
      "You should consider upgrading via the 'C:\\Users\\Fer_U\\PycharmProjects\\CyberattacksAttention\\venv\\Scripts\\python.exe -m pip install --upgrade pip' command.\n"
     ]
    }
   ],
   "source": [
    "!pip install neural_structured_learning"
   ],
   "metadata": {
    "collapsed": false,
    "pycharm": {
     "name": "#%%\n"
    }
   }
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Requirement already satisfied: scikit_learn in c:\\users\\fer_u\\pycharmprojects\\cyberattacksattention\\venv\\lib\\site-packages (1.2.0)\n",
      "Requirement already satisfied: threadpoolctl>=2.0.0 in c:\\users\\fer_u\\pycharmprojects\\cyberattacksattention\\venv\\lib\\site-packages (from scikit_learn) (3.1.0)\n",
      "Requirement already satisfied: joblib>=1.1.1 in c:\\users\\fer_u\\pycharmprojects\\cyberattacksattention\\venv\\lib\\site-packages (from scikit_learn) (1.2.0)\n",
      "Requirement already satisfied: scipy>=1.3.2 in c:\\users\\fer_u\\pycharmprojects\\cyberattacksattention\\venv\\lib\\site-packages (from scikit_learn) (1.9.3)\n",
      "Requirement already satisfied: numpy>=1.17.3 in c:\\users\\fer_u\\pycharmprojects\\cyberattacksattention\\venv\\lib\\site-packages (from scikit_learn) (1.23.5)\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "WARNING: You are using pip version 21.3.1; however, version 22.3.1 is available.\n",
      "You should consider upgrading via the 'C:\\Users\\Fer_U\\PycharmProjects\\CyberattacksAttention\\venv\\Scripts\\python.exe -m pip install --upgrade pip' command.\n"
     ]
    }
   ],
   "source": [
    "!pip install scikit_learn"
   ],
   "metadata": {
    "collapsed": false,
    "pycharm": {
     "name": "#%%\n"
    }
   }
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "executionInfo": {
     "elapsed": 4460,
     "status": "ok",
     "timestamp": 1670604423667,
     "user": {
      "displayName": "Fernando José Rendón Segador",
      "userId": "09288482551460164544"
     },
     "user_tz": -60
    },
    "id": "bTL3Ufo0t487",
    "pycharm": {
     "name": "#%%\n"
    }
   },
   "outputs": [],
   "source": [
    "import tensorflow as tf\n",
    "import pandas as pd\n",
    "import neural_structured_learning as nsl\n",
    "from sklearn.preprocessing import LabelEncoder\n",
    "from sklearn import preprocessing\n",
    "from sklearn.model_selection import *"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "executionInfo": {
     "elapsed": 1214,
     "status": "ok",
     "timestamp": 1670604426852,
     "user": {
      "displayName": "Fernando José Rendón Segador",
      "userId": "09288482551460164544"
     },
     "user_tz": -60
    },
    "id": "xdB9GixktNz0",
    "pycharm": {
     "name": "#%%\n"
    }
   },
   "outputs": [],
   "source": [
    "df = pd.read_csv('ICSX_URL_2017/Malware.csv')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 300
    },
    "executionInfo": {
     "elapsed": 14,
     "status": "ok",
     "timestamp": 1670604426856,
     "user": {
      "displayName": "Fernando José Rendón Segador",
      "userId": "09288482551460164544"
     },
     "user_tz": -60
    },
    "id": "856UWFEmyUms",
    "outputId": "a5a2bcaf-4a37-454e-eb77-2ffe6b9b956f",
    "pycharm": {
     "name": "#%%\n"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": "   Querylength  domain_token_count  path_token_count  avgdomaintokenlen  \\\n0            0                   2                12                5.5   \n1            0                   3                12                5.0   \n2            2                   2                11                4.0   \n3            0                   2                 7                4.5   \n4           19                   2                10                6.0   \n\n   longdomaintokenlen  avgpathtokenlen  tld  charcompvowels  charcompace  \\\n0                   8         4.083334    2              15            7   \n1                  10         3.583333    3              12            8   \n2                   5         4.750000    2              16           11   \n3                   7         5.714286    2              15           10   \n4                   9         2.250000    2               9            5   \n\n   ldl_url  ...  SymbolCount_FileName  SymbolCount_Extension  \\\n0        0  ...                    -1                     -1   \n1        2  ...                     1                      0   \n2        0  ...                     2                      0   \n3        0  ...                     0                      0   \n4        0  ...                     5                      4   \n\n   SymbolCount_Afterpath  Entropy_URL  Entropy_Domain  Entropy_DirectoryName  \\\n0                     -1     0.676804        0.860529              -1.000000   \n1                     -1     0.715629        0.776796               0.693127   \n2                      1     0.677701        1.000000               0.677704   \n3                     -1     0.696067        0.879588               0.818007   \n4                      3     0.747202        0.833700               0.655459   \n\n   Entropy_Filename  Entropy_Extension  Entropy_Afterpath  URL_Type_obf_Type  \n0         -1.000000           -1.00000          -1.000000             benign  \n1          0.738315            1.00000          -1.000000             benign  \n2          0.916667            0.00000           0.898227             benign  \n3          0.753585            0.00000          -1.000000             benign  \n4          0.829535            0.83615           0.823008             benign  \n\n[5 rows x 80 columns]",
      "text/html": "<div>\n<style scoped>\n    .dataframe tbody tr th:only-of-type {\n        vertical-align: middle;\n    }\n\n    .dataframe tbody tr th {\n        vertical-align: top;\n    }\n\n    .dataframe thead th {\n        text-align: right;\n    }\n</style>\n<table border=\"1\" class=\"dataframe\">\n  <thead>\n    <tr style=\"text-align: right;\">\n      <th></th>\n      <th>Querylength</th>\n      <th>domain_token_count</th>\n      <th>path_token_count</th>\n      <th>avgdomaintokenlen</th>\n      <th>longdomaintokenlen</th>\n      <th>avgpathtokenlen</th>\n      <th>tld</th>\n      <th>charcompvowels</th>\n      <th>charcompace</th>\n      <th>ldl_url</th>\n      <th>...</th>\n      <th>SymbolCount_FileName</th>\n      <th>SymbolCount_Extension</th>\n      <th>SymbolCount_Afterpath</th>\n      <th>Entropy_URL</th>\n      <th>Entropy_Domain</th>\n      <th>Entropy_DirectoryName</th>\n      <th>Entropy_Filename</th>\n      <th>Entropy_Extension</th>\n      <th>Entropy_Afterpath</th>\n      <th>URL_Type_obf_Type</th>\n    </tr>\n  </thead>\n  <tbody>\n    <tr>\n      <th>0</th>\n      <td>0</td>\n      <td>2</td>\n      <td>12</td>\n      <td>5.5</td>\n      <td>8</td>\n      <td>4.083334</td>\n      <td>2</td>\n      <td>15</td>\n      <td>7</td>\n      <td>0</td>\n      <td>...</td>\n      <td>-1</td>\n      <td>-1</td>\n      <td>-1</td>\n      <td>0.676804</td>\n      <td>0.860529</td>\n      <td>-1.000000</td>\n      <td>-1.000000</td>\n      <td>-1.00000</td>\n      <td>-1.000000</td>\n      <td>benign</td>\n    </tr>\n    <tr>\n      <th>1</th>\n      <td>0</td>\n      <td>3</td>\n      <td>12</td>\n      <td>5.0</td>\n      <td>10</td>\n      <td>3.583333</td>\n      <td>3</td>\n      <td>12</td>\n      <td>8</td>\n      <td>2</td>\n      <td>...</td>\n      <td>1</td>\n      <td>0</td>\n      <td>-1</td>\n      <td>0.715629</td>\n      <td>0.776796</td>\n      <td>0.693127</td>\n      <td>0.738315</td>\n      <td>1.00000</td>\n      <td>-1.000000</td>\n      <td>benign</td>\n    </tr>\n    <tr>\n      <th>2</th>\n      <td>2</td>\n      <td>2</td>\n      <td>11</td>\n      <td>4.0</td>\n      <td>5</td>\n      <td>4.750000</td>\n      <td>2</td>\n      <td>16</td>\n      <td>11</td>\n      <td>0</td>\n      <td>...</td>\n      <td>2</td>\n      <td>0</td>\n      <td>1</td>\n      <td>0.677701</td>\n      <td>1.000000</td>\n      <td>0.677704</td>\n      <td>0.916667</td>\n      <td>0.00000</td>\n      <td>0.898227</td>\n      <td>benign</td>\n    </tr>\n    <tr>\n      <th>3</th>\n      <td>0</td>\n      <td>2</td>\n      <td>7</td>\n      <td>4.5</td>\n      <td>7</td>\n      <td>5.714286</td>\n      <td>2</td>\n      <td>15</td>\n      <td>10</td>\n      <td>0</td>\n      <td>...</td>\n      <td>0</td>\n      <td>0</td>\n      <td>-1</td>\n      <td>0.696067</td>\n      <td>0.879588</td>\n      <td>0.818007</td>\n      <td>0.753585</td>\n      <td>0.00000</td>\n      <td>-1.000000</td>\n      <td>benign</td>\n    </tr>\n    <tr>\n      <th>4</th>\n      <td>19</td>\n      <td>2</td>\n      <td>10</td>\n      <td>6.0</td>\n      <td>9</td>\n      <td>2.250000</td>\n      <td>2</td>\n      <td>9</td>\n      <td>5</td>\n      <td>0</td>\n      <td>...</td>\n      <td>5</td>\n      <td>4</td>\n      <td>3</td>\n      <td>0.747202</td>\n      <td>0.833700</td>\n      <td>0.655459</td>\n      <td>0.829535</td>\n      <td>0.83615</td>\n      <td>0.823008</td>\n      <td>benign</td>\n    </tr>\n  </tbody>\n</table>\n<p>5 rows × 80 columns</p>\n</div>"
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {
    "executionInfo": {
     "elapsed": 9,
     "status": "ok",
     "timestamp": 1670604426856,
     "user": {
      "displayName": "Fernando José Rendón Segador",
      "userId": "09288482551460164544"
     },
     "user_tz": -60
    },
    "id": "mkez4dRDyZ4L",
    "pycharm": {
     "name": "#%%\n"
    }
   },
   "outputs": [],
   "source": [
    "features = len(df.columns) - 1\n",
    "label_encoder = LabelEncoder()\n",
    "df = df.dropna()\n",
    "df = df.reset_index(drop=True)\n",
    "df['URL_Type_obf_Type'] = label_encoder.fit_transform(df['URL_Type_obf_Type'])\n",
    "classes = df['URL_Type_obf_Type'].nunique()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 488
    },
    "executionInfo": {
     "elapsed": 10,
     "status": "ok",
     "timestamp": 1670604426857,
     "user": {
      "displayName": "Fernando José Rendón Segador",
      "userId": "09288482551460164544"
     },
     "user_tz": -60
    },
    "id": "6wz-53mHnm7p",
    "outputId": "fe64ae3c-8710-4fbe-fc93-ff39924faffd",
    "pycharm": {
     "name": "#%%\n"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": "      Querylength  domain_token_count  path_token_count  avgdomaintokenlen  \\\n0               0                   2                12           5.500000   \n1               0                   3                12           5.000000   \n2              19                   2                10           6.000000   \n3               0                   2                10           5.500000   \n4               0                   2                 9           2.500000   \n...           ...                 ...               ...                ...   \n7144            0                   2                 5           9.500000   \n7145            0                   3                 5           5.000000   \n7146            0                   4                 6           5.500000   \n7147            0                   3                 5           5.000000   \n7148            0                   3                 5           5.333334   \n\n      longdomaintokenlen  avgpathtokenlen  tld  charcompvowels  charcompace  \\\n0                      8         4.083334    2              15            7   \n1                     10         3.583333    3              12            8   \n2                      9         2.250000    2               9            5   \n3                      9         4.100000    2              15           11   \n4                      3         4.555555    2               6            3   \n...                  ...              ...  ...             ...          ...   \n7144                  16         5.000000    2               9            8   \n7145                  10         5.400000    3               9            7   \n7146                   9         3.000000    4               2            0   \n7147                  10         5.200000    3               6            3   \n7148                  11         4.800000    3               6            6   \n\n      ldl_url  ...  SymbolCount_FileName  SymbolCount_Extension  \\\n0           0  ...                    -1                     -1   \n1           2  ...                     1                      0   \n2           0  ...                     5                      4   \n3           0  ...                    -1                     -1   \n4           0  ...                     1                      0   \n...       ...  ...                   ...                    ...   \n7144        0  ...                     1                      0   \n7145        0  ...                     1                      0   \n7146        0  ...                     1                      0   \n7147        0  ...                     1                      0   \n7148        1  ...                     1                      0   \n\n      SymbolCount_Afterpath  Entropy_URL  Entropy_Domain  \\\n0                        -1     0.676804        0.860529   \n1                        -1     0.715629        0.776796   \n2                         3     0.747202        0.833700   \n3                        -1     0.732981        0.860529   \n4                        -1     0.742606        1.000000   \n...                     ...          ...             ...   \n7144                     -1     0.685060        0.791760   \n7145                     -1     0.785710        0.816442   \n7146                     -1     0.732703        0.797498   \n7147                     -1     0.776731        0.816442   \n7148                     -1     0.810975        0.893417   \n\n      Entropy_DirectoryName  Entropy_Filename  Entropy_Extension  \\\n0                 -1.000000         -1.000000           -1.00000   \n1                  0.693127          0.738315            1.00000   \n2                  0.655459          0.829535            0.83615   \n3                 -1.000000         -1.000000           -1.00000   \n4                  0.785719          0.808833            1.00000   \n...                     ...               ...                ...   \n7144               0.579380          0.794459            0.57938   \n7145               0.769934          0.820569            0.57938   \n7146               0.666667          0.887436            1.00000   \n7147               0.668414          0.893417            0.57938   \n7148               0.796490          0.781250            0.57938   \n\n      Entropy_Afterpath  URL_Type_obf_Type  \n0             -1.000000                  0  \n1             -1.000000                  0  \n2              0.823008                  0  \n3             -1.000000                  0  \n4             -1.000000                  0  \n...                 ...                ...  \n7144          -1.000000                  1  \n7145          -1.000000                  1  \n7146          -1.000000                  1  \n7147          -1.000000                  1  \n7148          -1.000000                  1  \n\n[7149 rows x 80 columns]",
      "text/html": "<div>\n<style scoped>\n    .dataframe tbody tr th:only-of-type {\n        vertical-align: middle;\n    }\n\n    .dataframe tbody tr th {\n        vertical-align: top;\n    }\n\n    .dataframe thead th {\n        text-align: right;\n    }\n</style>\n<table border=\"1\" class=\"dataframe\">\n  <thead>\n    <tr style=\"text-align: right;\">\n      <th></th>\n      <th>Querylength</th>\n      <th>domain_token_count</th>\n      <th>path_token_count</th>\n      <th>avgdomaintokenlen</th>\n      <th>longdomaintokenlen</th>\n      <th>avgpathtokenlen</th>\n      <th>tld</th>\n      <th>charcompvowels</th>\n      <th>charcompace</th>\n      <th>ldl_url</th>\n      <th>...</th>\n      <th>SymbolCount_FileName</th>\n      <th>SymbolCount_Extension</th>\n      <th>SymbolCount_Afterpath</th>\n      <th>Entropy_URL</th>\n      <th>Entropy_Domain</th>\n      <th>Entropy_DirectoryName</th>\n      <th>Entropy_Filename</th>\n      <th>Entropy_Extension</th>\n      <th>Entropy_Afterpath</th>\n      <th>URL_Type_obf_Type</th>\n    </tr>\n  </thead>\n  <tbody>\n    <tr>\n      <th>0</th>\n      <td>0</td>\n      <td>2</td>\n      <td>12</td>\n      <td>5.500000</td>\n      <td>8</td>\n      <td>4.083334</td>\n      <td>2</td>\n      <td>15</td>\n      <td>7</td>\n      <td>0</td>\n      <td>...</td>\n      <td>-1</td>\n      <td>-1</td>\n      <td>-1</td>\n      <td>0.676804</td>\n      <td>0.860529</td>\n      <td>-1.000000</td>\n      <td>-1.000000</td>\n      <td>-1.00000</td>\n      <td>-1.000000</td>\n      <td>0</td>\n    </tr>\n    <tr>\n      <th>1</th>\n      <td>0</td>\n      <td>3</td>\n      <td>12</td>\n      <td>5.000000</td>\n      <td>10</td>\n      <td>3.583333</td>\n      <td>3</td>\n      <td>12</td>\n      <td>8</td>\n      <td>2</td>\n      <td>...</td>\n      <td>1</td>\n      <td>0</td>\n      <td>-1</td>\n      <td>0.715629</td>\n      <td>0.776796</td>\n      <td>0.693127</td>\n      <td>0.738315</td>\n      <td>1.00000</td>\n      <td>-1.000000</td>\n      <td>0</td>\n    </tr>\n    <tr>\n      <th>2</th>\n      <td>19</td>\n      <td>2</td>\n      <td>10</td>\n      <td>6.000000</td>\n      <td>9</td>\n      <td>2.250000</td>\n      <td>2</td>\n      <td>9</td>\n      <td>5</td>\n      <td>0</td>\n      <td>...</td>\n      <td>5</td>\n      <td>4</td>\n      <td>3</td>\n      <td>0.747202</td>\n      <td>0.833700</td>\n      <td>0.655459</td>\n      <td>0.829535</td>\n      <td>0.83615</td>\n      <td>0.823008</td>\n      <td>0</td>\n    </tr>\n    <tr>\n      <th>3</th>\n      <td>0</td>\n      <td>2</td>\n      <td>10</td>\n      <td>5.500000</td>\n      <td>9</td>\n      <td>4.100000</td>\n      <td>2</td>\n      <td>15</td>\n      <td>11</td>\n      <td>0</td>\n      <td>...</td>\n      <td>-1</td>\n      <td>-1</td>\n      <td>-1</td>\n      <td>0.732981</td>\n      <td>0.860529</td>\n      <td>-1.000000</td>\n      <td>-1.000000</td>\n      <td>-1.00000</td>\n      <td>-1.000000</td>\n      <td>0</td>\n    </tr>\n    <tr>\n      <th>4</th>\n      <td>0</td>\n      <td>2</td>\n      <td>9</td>\n      <td>2.500000</td>\n      <td>3</td>\n      <td>4.555555</td>\n      <td>2</td>\n      <td>6</td>\n      <td>3</td>\n      <td>0</td>\n      <td>...</td>\n      <td>1</td>\n      <td>0</td>\n      <td>-1</td>\n      <td>0.742606</td>\n      <td>1.000000</td>\n      <td>0.785719</td>\n      <td>0.808833</td>\n      <td>1.00000</td>\n      <td>-1.000000</td>\n      <td>0</td>\n    </tr>\n    <tr>\n      <th>...</th>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n    </tr>\n    <tr>\n      <th>7144</th>\n      <td>0</td>\n      <td>2</td>\n      <td>5</td>\n      <td>9.500000</td>\n      <td>16</td>\n      <td>5.000000</td>\n      <td>2</td>\n      <td>9</td>\n      <td>8</td>\n      <td>0</td>\n      <td>...</td>\n      <td>1</td>\n      <td>0</td>\n      <td>-1</td>\n      <td>0.685060</td>\n      <td>0.791760</td>\n      <td>0.579380</td>\n      <td>0.794459</td>\n      <td>0.57938</td>\n      <td>-1.000000</td>\n      <td>1</td>\n    </tr>\n    <tr>\n      <th>7145</th>\n      <td>0</td>\n      <td>3</td>\n      <td>5</td>\n      <td>5.000000</td>\n      <td>10</td>\n      <td>5.400000</td>\n      <td>3</td>\n      <td>9</td>\n      <td>7</td>\n      <td>0</td>\n      <td>...</td>\n      <td>1</td>\n      <td>0</td>\n      <td>-1</td>\n      <td>0.785710</td>\n      <td>0.816442</td>\n      <td>0.769934</td>\n      <td>0.820569</td>\n      <td>0.57938</td>\n      <td>-1.000000</td>\n      <td>1</td>\n    </tr>\n    <tr>\n      <th>7146</th>\n      <td>0</td>\n      <td>4</td>\n      <td>6</td>\n      <td>5.500000</td>\n      <td>9</td>\n      <td>3.000000</td>\n      <td>4</td>\n      <td>2</td>\n      <td>0</td>\n      <td>0</td>\n      <td>...</td>\n      <td>1</td>\n      <td>0</td>\n      <td>-1</td>\n      <td>0.732703</td>\n      <td>0.797498</td>\n      <td>0.666667</td>\n      <td>0.887436</td>\n      <td>1.00000</td>\n      <td>-1.000000</td>\n      <td>1</td>\n    </tr>\n    <tr>\n      <th>7147</th>\n      <td>0</td>\n      <td>3</td>\n      <td>5</td>\n      <td>5.000000</td>\n      <td>10</td>\n      <td>5.200000</td>\n      <td>3</td>\n      <td>6</td>\n      <td>3</td>\n      <td>0</td>\n      <td>...</td>\n      <td>1</td>\n      <td>0</td>\n      <td>-1</td>\n      <td>0.776731</td>\n      <td>0.816442</td>\n      <td>0.668414</td>\n      <td>0.893417</td>\n      <td>0.57938</td>\n      <td>-1.000000</td>\n      <td>1</td>\n    </tr>\n    <tr>\n      <th>7148</th>\n      <td>0</td>\n      <td>3</td>\n      <td>5</td>\n      <td>5.333334</td>\n      <td>11</td>\n      <td>4.800000</td>\n      <td>3</td>\n      <td>6</td>\n      <td>6</td>\n      <td>1</td>\n      <td>...</td>\n      <td>1</td>\n      <td>0</td>\n      <td>-1</td>\n      <td>0.810975</td>\n      <td>0.893417</td>\n      <td>0.796490</td>\n      <td>0.781250</td>\n      <td>0.57938</td>\n      <td>-1.000000</td>\n      <td>1</td>\n    </tr>\n  </tbody>\n</table>\n<p>7149 rows × 80 columns</p>\n</div>"
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 331
    },
    "executionInfo": {
     "elapsed": 9,
     "status": "ok",
     "timestamp": 1670604426857,
     "user": {
      "displayName": "Fernando José Rendón Segador",
      "userId": "09288482551460164544"
     },
     "user_tz": -60
    },
    "id": "pDdBjmOgVZdA",
    "outputId": "649a90de-aad7-4207-a533-07f3a793c1d5",
    "pycharm": {
     "name": "#%%\n"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": "                   Querylength  domain_token_count  path_token_count  \\\nURL_Type_obf_Type                                                      \n0                         2709                2709              2709   \n1                         4440                4440              4440   \n\n                   avgdomaintokenlen  longdomaintokenlen  avgpathtokenlen  \\\nURL_Type_obf_Type                                                           \n0                               2709                2709             2709   \n1                               4440                4440             4440   \n\n                    tld  charcompvowels  charcompace  ldl_url  ...  \\\nURL_Type_obf_Type                                              ...   \n0                  2709            2709         2709     2709  ...   \n1                  4440            4440         4440     4440  ...   \n\n                   SymbolCount_Directoryname  SymbolCount_FileName  \\\nURL_Type_obf_Type                                                    \n0                                       2709                  2709   \n1                                       4440                  4440   \n\n                   SymbolCount_Extension  SymbolCount_Afterpath  Entropy_URL  \\\nURL_Type_obf_Type                                                              \n0                                   2709                   2709         2709   \n1                                   4440                   4440         4440   \n\n                   Entropy_Domain  Entropy_DirectoryName  Entropy_Filename  \\\nURL_Type_obf_Type                                                            \n0                            2709                   2709              2709   \n1                            4440                   4440              4440   \n\n                   Entropy_Extension  Entropy_Afterpath  \nURL_Type_obf_Type                                        \n0                               2709               2709  \n1                               4440               4440  \n\n[2 rows x 79 columns]",
      "text/html": "<div>\n<style scoped>\n    .dataframe tbody tr th:only-of-type {\n        vertical-align: middle;\n    }\n\n    .dataframe tbody tr th {\n        vertical-align: top;\n    }\n\n    .dataframe thead th {\n        text-align: right;\n    }\n</style>\n<table border=\"1\" class=\"dataframe\">\n  <thead>\n    <tr style=\"text-align: right;\">\n      <th></th>\n      <th>Querylength</th>\n      <th>domain_token_count</th>\n      <th>path_token_count</th>\n      <th>avgdomaintokenlen</th>\n      <th>longdomaintokenlen</th>\n      <th>avgpathtokenlen</th>\n      <th>tld</th>\n      <th>charcompvowels</th>\n      <th>charcompace</th>\n      <th>ldl_url</th>\n      <th>...</th>\n      <th>SymbolCount_Directoryname</th>\n      <th>SymbolCount_FileName</th>\n      <th>SymbolCount_Extension</th>\n      <th>SymbolCount_Afterpath</th>\n      <th>Entropy_URL</th>\n      <th>Entropy_Domain</th>\n      <th>Entropy_DirectoryName</th>\n      <th>Entropy_Filename</th>\n      <th>Entropy_Extension</th>\n      <th>Entropy_Afterpath</th>\n    </tr>\n    <tr>\n      <th>URL_Type_obf_Type</th>\n      <th></th>\n      <th></th>\n      <th></th>\n      <th></th>\n      <th></th>\n      <th></th>\n      <th></th>\n      <th></th>\n      <th></th>\n      <th></th>\n      <th></th>\n      <th></th>\n      <th></th>\n      <th></th>\n      <th></th>\n      <th></th>\n      <th></th>\n      <th></th>\n      <th></th>\n      <th></th>\n      <th></th>\n    </tr>\n  </thead>\n  <tbody>\n    <tr>\n      <th>0</th>\n      <td>2709</td>\n      <td>2709</td>\n      <td>2709</td>\n      <td>2709</td>\n      <td>2709</td>\n      <td>2709</td>\n      <td>2709</td>\n      <td>2709</td>\n      <td>2709</td>\n      <td>2709</td>\n      <td>...</td>\n      <td>2709</td>\n      <td>2709</td>\n      <td>2709</td>\n      <td>2709</td>\n      <td>2709</td>\n      <td>2709</td>\n      <td>2709</td>\n      <td>2709</td>\n      <td>2709</td>\n      <td>2709</td>\n    </tr>\n    <tr>\n      <th>1</th>\n      <td>4440</td>\n      <td>4440</td>\n      <td>4440</td>\n      <td>4440</td>\n      <td>4440</td>\n      <td>4440</td>\n      <td>4440</td>\n      <td>4440</td>\n      <td>4440</td>\n      <td>4440</td>\n      <td>...</td>\n      <td>4440</td>\n      <td>4440</td>\n      <td>4440</td>\n      <td>4440</td>\n      <td>4440</td>\n      <td>4440</td>\n      <td>4440</td>\n      <td>4440</td>\n      <td>4440</td>\n      <td>4440</td>\n    </tr>\n  </tbody>\n</table>\n<p>2 rows × 79 columns</p>\n</div>"
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.groupby('URL_Type_obf_Type').count()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {
    "executionInfo": {
     "elapsed": 8,
     "status": "ok",
     "timestamp": 1670604426857,
     "user": {
      "displayName": "Fernando José Rendón Segador",
      "userId": "09288482551460164544"
     },
     "user_tz": -60
    },
    "id": "5MKUhTHEVvn8",
    "pycharm": {
     "name": "#%%\n"
    }
   },
   "outputs": [],
   "source": [
    "df_0 = df.loc[df['URL_Type_obf_Type'] == 0]\n",
    "df_1 = df.loc[df['URL_Type_obf_Type'] == 1]\n",
    "df_2 = df.loc[df['URL_Type_obf_Type'] == 2]\n",
    "df_3 = df.loc[df['URL_Type_obf_Type'] == 3]\n",
    "df_4 = df.loc[df['URL_Type_obf_Type'] == 4]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 488
    },
    "executionInfo": {
     "elapsed": 413,
     "status": "ok",
     "timestamp": 1670604427263,
     "user": {
      "displayName": "Fernando José Rendón Segador",
      "userId": "09288482551460164544"
     },
     "user_tz": -60
    },
    "id": "VBg_I0QKXFk0",
    "outputId": "761a2fc5-02e5-46f0-eb8a-f7fd4f9bc9a0",
    "pycharm": {
     "name": "#%%\n"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": "      Querylength  domain_token_count  path_token_count  avgdomaintokenlen  \\\n0               0                   2                12           5.500000   \n1               0                   3                12           5.000000   \n2              19                   2                10           6.000000   \n3               0                   2                10           5.500000   \n4               0                   2                 9           2.500000   \n...           ...                 ...               ...                ...   \n7144            0                   2                 5           9.500000   \n7145            0                   3                 5           5.000000   \n7146            0                   4                 6           5.500000   \n7147            0                   3                 5           5.000000   \n7148            0                   3                 5           5.333334   \n\n      longdomaintokenlen  avgpathtokenlen  tld  charcompvowels  charcompace  \\\n0                      8         4.083334    2              15            7   \n1                     10         3.583333    3              12            8   \n2                      9         2.250000    2               9            5   \n3                      9         4.100000    2              15           11   \n4                      3         4.555555    2               6            3   \n...                  ...              ...  ...             ...          ...   \n7144                  16         5.000000    2               9            8   \n7145                  10         5.400000    3               9            7   \n7146                   9         3.000000    4               2            0   \n7147                  10         5.200000    3               6            3   \n7148                  11         4.800000    3               6            6   \n\n      ldl_url  ...  SymbolCount_FileName  SymbolCount_Extension  \\\n0           0  ...                    -1                     -1   \n1           2  ...                     1                      0   \n2           0  ...                     5                      4   \n3           0  ...                    -1                     -1   \n4           0  ...                     1                      0   \n...       ...  ...                   ...                    ...   \n7144        0  ...                     1                      0   \n7145        0  ...                     1                      0   \n7146        0  ...                     1                      0   \n7147        0  ...                     1                      0   \n7148        1  ...                     1                      0   \n\n      SymbolCount_Afterpath  Entropy_URL  Entropy_Domain  \\\n0                        -1     0.676804        0.860529   \n1                        -1     0.715629        0.776796   \n2                         3     0.747202        0.833700   \n3                        -1     0.732981        0.860529   \n4                        -1     0.742606        1.000000   \n...                     ...          ...             ...   \n7144                     -1     0.685060        0.791760   \n7145                     -1     0.785710        0.816442   \n7146                     -1     0.732703        0.797498   \n7147                     -1     0.776731        0.816442   \n7148                     -1     0.810975        0.893417   \n\n      Entropy_DirectoryName  Entropy_Filename  Entropy_Extension  \\\n0                 -1.000000         -1.000000           -1.00000   \n1                  0.693127          0.738315            1.00000   \n2                  0.655459          0.829535            0.83615   \n3                 -1.000000         -1.000000           -1.00000   \n4                  0.785719          0.808833            1.00000   \n...                     ...               ...                ...   \n7144               0.579380          0.794459            0.57938   \n7145               0.769934          0.820569            0.57938   \n7146               0.666667          0.887436            1.00000   \n7147               0.668414          0.893417            0.57938   \n7148               0.796490          0.781250            0.57938   \n\n      Entropy_Afterpath  URL_Type_obf_Type  \n0             -1.000000                  0  \n1             -1.000000                  0  \n2              0.823008                  0  \n3             -1.000000                  0  \n4             -1.000000                  0  \n...                 ...                ...  \n7144          -1.000000                  1  \n7145          -1.000000                  1  \n7146          -1.000000                  1  \n7147          -1.000000                  1  \n7148          -1.000000                  1  \n\n[7149 rows x 80 columns]",
      "text/html": "<div>\n<style scoped>\n    .dataframe tbody tr th:only-of-type {\n        vertical-align: middle;\n    }\n\n    .dataframe tbody tr th {\n        vertical-align: top;\n    }\n\n    .dataframe thead th {\n        text-align: right;\n    }\n</style>\n<table border=\"1\" class=\"dataframe\">\n  <thead>\n    <tr style=\"text-align: right;\">\n      <th></th>\n      <th>Querylength</th>\n      <th>domain_token_count</th>\n      <th>path_token_count</th>\n      <th>avgdomaintokenlen</th>\n      <th>longdomaintokenlen</th>\n      <th>avgpathtokenlen</th>\n      <th>tld</th>\n      <th>charcompvowels</th>\n      <th>charcompace</th>\n      <th>ldl_url</th>\n      <th>...</th>\n      <th>SymbolCount_FileName</th>\n      <th>SymbolCount_Extension</th>\n      <th>SymbolCount_Afterpath</th>\n      <th>Entropy_URL</th>\n      <th>Entropy_Domain</th>\n      <th>Entropy_DirectoryName</th>\n      <th>Entropy_Filename</th>\n      <th>Entropy_Extension</th>\n      <th>Entropy_Afterpath</th>\n      <th>URL_Type_obf_Type</th>\n    </tr>\n  </thead>\n  <tbody>\n    <tr>\n      <th>0</th>\n      <td>0</td>\n      <td>2</td>\n      <td>12</td>\n      <td>5.500000</td>\n      <td>8</td>\n      <td>4.083334</td>\n      <td>2</td>\n      <td>15</td>\n      <td>7</td>\n      <td>0</td>\n      <td>...</td>\n      <td>-1</td>\n      <td>-1</td>\n      <td>-1</td>\n      <td>0.676804</td>\n      <td>0.860529</td>\n      <td>-1.000000</td>\n      <td>-1.000000</td>\n      <td>-1.00000</td>\n      <td>-1.000000</td>\n      <td>0</td>\n    </tr>\n    <tr>\n      <th>1</th>\n      <td>0</td>\n      <td>3</td>\n      <td>12</td>\n      <td>5.000000</td>\n      <td>10</td>\n      <td>3.583333</td>\n      <td>3</td>\n      <td>12</td>\n      <td>8</td>\n      <td>2</td>\n      <td>...</td>\n      <td>1</td>\n      <td>0</td>\n      <td>-1</td>\n      <td>0.715629</td>\n      <td>0.776796</td>\n      <td>0.693127</td>\n      <td>0.738315</td>\n      <td>1.00000</td>\n      <td>-1.000000</td>\n      <td>0</td>\n    </tr>\n    <tr>\n      <th>2</th>\n      <td>19</td>\n      <td>2</td>\n      <td>10</td>\n      <td>6.000000</td>\n      <td>9</td>\n      <td>2.250000</td>\n      <td>2</td>\n      <td>9</td>\n      <td>5</td>\n      <td>0</td>\n      <td>...</td>\n      <td>5</td>\n      <td>4</td>\n      <td>3</td>\n      <td>0.747202</td>\n      <td>0.833700</td>\n      <td>0.655459</td>\n      <td>0.829535</td>\n      <td>0.83615</td>\n      <td>0.823008</td>\n      <td>0</td>\n    </tr>\n    <tr>\n      <th>3</th>\n      <td>0</td>\n      <td>2</td>\n      <td>10</td>\n      <td>5.500000</td>\n      <td>9</td>\n      <td>4.100000</td>\n      <td>2</td>\n      <td>15</td>\n      <td>11</td>\n      <td>0</td>\n      <td>...</td>\n      <td>-1</td>\n      <td>-1</td>\n      <td>-1</td>\n      <td>0.732981</td>\n      <td>0.860529</td>\n      <td>-1.000000</td>\n      <td>-1.000000</td>\n      <td>-1.00000</td>\n      <td>-1.000000</td>\n      <td>0</td>\n    </tr>\n    <tr>\n      <th>4</th>\n      <td>0</td>\n      <td>2</td>\n      <td>9</td>\n      <td>2.500000</td>\n      <td>3</td>\n      <td>4.555555</td>\n      <td>2</td>\n      <td>6</td>\n      <td>3</td>\n      <td>0</td>\n      <td>...</td>\n      <td>1</td>\n      <td>0</td>\n      <td>-1</td>\n      <td>0.742606</td>\n      <td>1.000000</td>\n      <td>0.785719</td>\n      <td>0.808833</td>\n      <td>1.00000</td>\n      <td>-1.000000</td>\n      <td>0</td>\n    </tr>\n    <tr>\n      <th>...</th>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n    </tr>\n    <tr>\n      <th>7144</th>\n      <td>0</td>\n      <td>2</td>\n      <td>5</td>\n      <td>9.500000</td>\n      <td>16</td>\n      <td>5.000000</td>\n      <td>2</td>\n      <td>9</td>\n      <td>8</td>\n      <td>0</td>\n      <td>...</td>\n      <td>1</td>\n      <td>0</td>\n      <td>-1</td>\n      <td>0.685060</td>\n      <td>0.791760</td>\n      <td>0.579380</td>\n      <td>0.794459</td>\n      <td>0.57938</td>\n      <td>-1.000000</td>\n      <td>1</td>\n    </tr>\n    <tr>\n      <th>7145</th>\n      <td>0</td>\n      <td>3</td>\n      <td>5</td>\n      <td>5.000000</td>\n      <td>10</td>\n      <td>5.400000</td>\n      <td>3</td>\n      <td>9</td>\n      <td>7</td>\n      <td>0</td>\n      <td>...</td>\n      <td>1</td>\n      <td>0</td>\n      <td>-1</td>\n      <td>0.785710</td>\n      <td>0.816442</td>\n      <td>0.769934</td>\n      <td>0.820569</td>\n      <td>0.57938</td>\n      <td>-1.000000</td>\n      <td>1</td>\n    </tr>\n    <tr>\n      <th>7146</th>\n      <td>0</td>\n      <td>4</td>\n      <td>6</td>\n      <td>5.500000</td>\n      <td>9</td>\n      <td>3.000000</td>\n      <td>4</td>\n      <td>2</td>\n      <td>0</td>\n      <td>0</td>\n      <td>...</td>\n      <td>1</td>\n      <td>0</td>\n      <td>-1</td>\n      <td>0.732703</td>\n      <td>0.797498</td>\n      <td>0.666667</td>\n      <td>0.887436</td>\n      <td>1.00000</td>\n      <td>-1.000000</td>\n      <td>1</td>\n    </tr>\n    <tr>\n      <th>7147</th>\n      <td>0</td>\n      <td>3</td>\n      <td>5</td>\n      <td>5.000000</td>\n      <td>10</td>\n      <td>5.200000</td>\n      <td>3</td>\n      <td>6</td>\n      <td>3</td>\n      <td>0</td>\n      <td>...</td>\n      <td>1</td>\n      <td>0</td>\n      <td>-1</td>\n      <td>0.776731</td>\n      <td>0.816442</td>\n      <td>0.668414</td>\n      <td>0.893417</td>\n      <td>0.57938</td>\n      <td>-1.000000</td>\n      <td>1</td>\n    </tr>\n    <tr>\n      <th>7148</th>\n      <td>0</td>\n      <td>3</td>\n      <td>5</td>\n      <td>5.333334</td>\n      <td>11</td>\n      <td>4.800000</td>\n      <td>3</td>\n      <td>6</td>\n      <td>6</td>\n      <td>1</td>\n      <td>...</td>\n      <td>1</td>\n      <td>0</td>\n      <td>-1</td>\n      <td>0.810975</td>\n      <td>0.893417</td>\n      <td>0.796490</td>\n      <td>0.781250</td>\n      <td>0.57938</td>\n      <td>-1.000000</td>\n      <td>1</td>\n    </tr>\n  </tbody>\n</table>\n<p>7149 rows × 80 columns</p>\n</div>"
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df = pd.concat([df_0, df_1, df_2, df_3, df_4])\n",
    "df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {
    "executionInfo": {
     "elapsed": 4,
     "status": "ok",
     "timestamp": 1670604427264,
     "user": {
      "displayName": "Fernando José Rendón Segador",
      "userId": "09288482551460164544"
     },
     "user_tz": -60
    },
    "id": "9s_HaYjkzuKk",
    "pycharm": {
     "name": "#%%\n"
    }
   },
   "outputs": [],
   "source": [
    "y = df.pop('URL_Type_obf_Type')\n",
    "X = df\n",
    "\n",
    "normalizer_scaler = preprocessing.Normalizer()\n",
    "x_scaled = normalizer_scaler.fit_transform(X)\n",
    "X = pd.DataFrame(x_scaled)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {
    "executionInfo": {
     "elapsed": 4,
     "status": "ok",
     "timestamp": 1670604427264,
     "user": {
      "displayName": "Fernando José Rendón Segador",
      "userId": "09288482551460164544"
     },
     "user_tz": -60
    },
    "id": "l-9LdOome2ck",
    "pycharm": {
     "name": "#%%\n"
    }
   },
   "outputs": [],
   "source": [
    "X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.20, random_state=42)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {
    "executionInfo": {
     "elapsed": 3,
     "status": "ok",
     "timestamp": 1670604427264,
     "user": {
      "displayName": "Fernando José Rendón Segador",
      "userId": "09288482551460164544"
     },
     "user_tz": -60
    },
    "id": "FC6lXk4Az3yB",
    "pycharm": {
     "name": "#%%\n"
    }
   },
   "outputs": [],
   "source": [
    "X_train = tf.convert_to_tensor(X_train)\n",
    "y_train = tf.convert_to_tensor(y_train)\n",
    "\n",
    "X_test = tf.convert_to_tensor(X_test)\n",
    "y_test = tf.convert_to_tensor(y_test)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {
    "executionInfo": {
     "elapsed": 333,
     "status": "ok",
     "timestamp": 1670604427594,
     "user": {
      "displayName": "Fernando José Rendón Segador",
      "userId": "09288482551460164544"
     },
     "user_tz": -60
    },
    "id": "SP8ckOayytne",
    "pycharm": {
     "name": "#%%\n"
    }
   },
   "outputs": [],
   "source": [
    "input = tf.keras.layers.Input((features,), name='feature')\n",
    "\n",
    "n1 = tf.keras.layers.Dense(32)(input)\n",
    "n1 = tf.keras.layers.Dropout(0.25)(n1)\n",
    "n1 = tf.keras.layers.Dense(64)(n1)\n",
    "n1 = tf.keras.layers.Dropout(0.25)(n1)\n",
    "n1 = tf.keras.layers.Dense(128)(n1)\n",
    "n1 = tf.keras.layers.Dropout(0.25)(n1)\n",
    "n1 = tf.keras.layers.Dense(256)(n1)\n",
    "\n",
    "n1 = tf.keras.layers.MultiHeadAttention(num_heads=int(256/8), key_dim=256, value_dim=256, attention_axes=1)(n1, n1, n1)\n",
    "\n",
    "n1 = tf.keras.layers.Dense(256)(n1)\n",
    "n1 = tf.keras.layers.Dropout(0.25)(n1)\n",
    "n1 = tf.keras.layers.Dense(128)(n1)\n",
    "n1 = tf.keras.layers.Dropout(0.25)(n1)\n",
    "n1 = tf.keras.layers.Dense(64)(n1)\n",
    "n1 = tf.keras.layers.Dropout(0.25)(n1)\n",
    "n1 = tf.keras.layers.Dense(32)(n1)\n",
    "\n",
    "output = tf.keras.layers.Dense(classes, activation='softmax')(n1)\n",
    "\n",
    "model = tf.keras.Model(inputs=input, outputs=output)\n",
    "\n",
    "adv_config = nsl.configs.make_adv_reg_config(multiplier=0.2, adv_step_size=0.05)\n",
    "adv_model = nsl.keras.AdversarialRegularization(model, adv_config=adv_config)\n",
    "\n",
    "# Compile, train, and evaluate.\n",
    "adv_model.compile(optimizer='adam',\n",
    "                  loss='sparse_categorical_crossentropy',\n",
    "                  metrics=['accuracy'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/"
    },
    "executionInfo": {
     "elapsed": 269,
     "status": "ok",
     "timestamp": 1670604427855,
     "user": {
      "displayName": "Fernando José Rendón Segador",
      "userId": "09288482551460164544"
     },
     "user_tz": -60
    },
    "id": "-EUxz4vRy7YP",
    "outputId": "1c8c1a81-6e6b-4129-f8a2-9d22f904cb87",
    "pycharm": {
     "name": "#%%\n"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Model: \"model\"\n",
      "__________________________________________________________________________________________________\n",
      " Layer (type)                   Output Shape         Param #     Connected to                     \n",
      "==================================================================================================\n",
      " feature (InputLayer)           [(None, 79)]         0           []                               \n",
      "                                                                                                  \n",
      " dense (Dense)                  (None, 32)           2560        ['feature[0][0]']                \n",
      "                                                                                                  \n",
      " dropout (Dropout)              (None, 32)           0           ['dense[0][0]']                  \n",
      "                                                                                                  \n",
      " dense_1 (Dense)                (None, 64)           2112        ['dropout[0][0]']                \n",
      "                                                                                                  \n",
      " dropout_1 (Dropout)            (None, 64)           0           ['dense_1[0][0]']                \n",
      "                                                                                                  \n",
      " dense_2 (Dense)                (None, 128)          8320        ['dropout_1[0][0]']              \n",
      "                                                                                                  \n",
      " dropout_2 (Dropout)            (None, 128)          0           ['dense_2[0][0]']                \n",
      "                                                                                                  \n",
      " dense_3 (Dense)                (None, 256)          33024       ['dropout_2[0][0]']              \n",
      "                                                                                                  \n",
      " multi_head_attention (MultiHea  (None, 256)         8413440     ['dense_3[0][0]',                \n",
      " dAttention)                                                      'dense_3[0][0]',                \n",
      "                                                                  'dense_3[0][0]']                \n",
      "                                                                                                  \n",
      " dense_4 (Dense)                (None, 256)          65792       ['multi_head_attention[0][0]']   \n",
      "                                                                                                  \n",
      " dropout_3 (Dropout)            (None, 256)          0           ['dense_4[0][0]']                \n",
      "                                                                                                  \n",
      " dense_5 (Dense)                (None, 128)          32896       ['dropout_3[0][0]']              \n",
      "                                                                                                  \n",
      " dropout_4 (Dropout)            (None, 128)          0           ['dense_5[0][0]']                \n",
      "                                                                                                  \n",
      " dense_6 (Dense)                (None, 64)           8256        ['dropout_4[0][0]']              \n",
      "                                                                                                  \n",
      " dropout_5 (Dropout)            (None, 64)           0           ['dense_6[0][0]']                \n",
      "                                                                                                  \n",
      " dense_7 (Dense)                (None, 32)           2080        ['dropout_5[0][0]']              \n",
      "                                                                                                  \n",
      " dense_8 (Dense)                (None, 2)            66          ['dense_7[0][0]']                \n",
      "                                                                                                  \n",
      "==================================================================================================\n",
      "Total params: 8,568,546\n",
      "Trainable params: 8,568,546\n",
      "Non-trainable params: 0\n",
      "__________________________________________________________________________________________________\n"
     ]
    }
   ],
   "source": [
    "model.summary()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 48
    },
    "executionInfo": {
     "elapsed": 447,
     "status": "ok",
     "timestamp": 1670604428298,
     "user": {
      "displayName": "Fernando José Rendón Segador",
      "userId": "09288482551460164544"
     },
     "user_tz": -60
    },
    "id": "844W7YPn82Gw",
    "outputId": "ea88bcec-2ee8-4229-e43f-6c1a767fdc89",
    "pycharm": {
     "name": "#%%\n"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "You must install pydot (`pip install pydot`) and install graphviz (see instructions at https://graphviz.gitlab.io/download/) for plot_model to work.\n"
     ]
    }
   ],
   "source": [
    "tf.keras.utils.plot_model(model, \n",
    "                          show_shapes=True,\n",
    "                          show_dtype=True,\n",
    "                          show_layer_names=True,\n",
    "                          rankdir='LR')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/"
    },
    "id": "RjM9Xf2Ry-lq",
    "outputId": "3f4f80c6-a5ac-4e5e-8981-be5081cd7e3c",
    "pycharm": {
     "name": "#%%\n"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 1/1000\n",
      "WARNING:tensorflow:From C:\\Users\\Fer_U\\PycharmProjects\\CyberattacksAttention\\venv\\lib\\site-packages\\tensorflow\\python\\autograph\\pyct\\static_analysis\\liveness.py:83: Analyzer.lamba_check (from tensorflow.python.autograph.pyct.static_analysis.liveness) is deprecated and will be removed after 2023-09-23.\n",
      "Instructions for updating:\n",
      "Lambda fuctions will be no more assumed to be used in the statement where they are used, or at least in the same block. https://github.com/tensorflow/tensorflow/issues/56089\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "WARNING:absl:Cannot perturb non-Tensor input: dict_keys(['label'])\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "12/12 [==============================] - 9s 378ms/step - loss: 1.0297 - sparse_categorical_crossentropy: 0.8424 - sparse_categorical_accuracy: 0.5688 - scaled_adversarial_loss: 0.1873 - val_loss: 0.7949 - val_sparse_categorical_crossentropy: 0.6511 - val_sparse_categorical_accuracy: 0.6916 - val_scaled_adversarial_loss: 0.1438\n",
      "Epoch 2/1000\n",
      "12/12 [==============================] - 4s 373ms/step - loss: 0.7641 - sparse_categorical_crossentropy: 0.6167 - sparse_categorical_accuracy: 0.6763 - scaled_adversarial_loss: 0.1475 - val_loss: 0.7264 - val_sparse_categorical_crossentropy: 0.5825 - val_sparse_categorical_accuracy: 0.6944 - val_scaled_adversarial_loss: 0.1438\n",
      "Epoch 3/1000\n",
      "12/12 [==============================] - 4s 352ms/step - loss: 0.7253 - sparse_categorical_crossentropy: 0.5808 - sparse_categorical_accuracy: 0.7139 - scaled_adversarial_loss: 0.1445 - val_loss: 0.6761 - val_sparse_categorical_crossentropy: 0.5232 - val_sparse_categorical_accuracy: 0.7448 - val_scaled_adversarial_loss: 0.1529\n",
      "Epoch 4/1000\n",
      "12/12 [==============================] - 4s 364ms/step - loss: 0.6846 - sparse_categorical_crossentropy: 0.5395 - sparse_categorical_accuracy: 0.7311 - scaled_adversarial_loss: 0.1452 - val_loss: 0.6500 - val_sparse_categorical_crossentropy: 0.4884 - val_sparse_categorical_accuracy: 0.7545 - val_scaled_adversarial_loss: 0.1615\n",
      "Epoch 5/1000\n",
      "12/12 [==============================] - 4s 365ms/step - loss: 0.6665 - sparse_categorical_crossentropy: 0.5141 - sparse_categorical_accuracy: 0.7575 - scaled_adversarial_loss: 0.1524 - val_loss: 0.6242 - val_sparse_categorical_crossentropy: 0.4611 - val_sparse_categorical_accuracy: 0.7552 - val_scaled_adversarial_loss: 0.1631\n",
      "Epoch 6/1000\n",
      "12/12 [==============================] - 5s 382ms/step - loss: 0.6423 - sparse_categorical_crossentropy: 0.4888 - sparse_categorical_accuracy: 0.7764 - scaled_adversarial_loss: 0.1535 - val_loss: 0.6097 - val_sparse_categorical_crossentropy: 0.4189 - val_sparse_categorical_accuracy: 0.8189 - val_scaled_adversarial_loss: 0.1908\n",
      "Epoch 7/1000\n",
      "12/12 [==============================] - 4s 354ms/step - loss: 0.6344 - sparse_categorical_crossentropy: 0.4734 - sparse_categorical_accuracy: 0.7832 - scaled_adversarial_loss: 0.1609 - val_loss: 0.5992 - val_sparse_categorical_crossentropy: 0.4265 - val_sparse_categorical_accuracy: 0.7839 - val_scaled_adversarial_loss: 0.1728\n",
      "Epoch 8/1000\n",
      "12/12 [==============================] - 4s 355ms/step - loss: 0.6177 - sparse_categorical_crossentropy: 0.4566 - sparse_categorical_accuracy: 0.7895 - scaled_adversarial_loss: 0.1612 - val_loss: 0.5891 - val_sparse_categorical_crossentropy: 0.4009 - val_sparse_categorical_accuracy: 0.8098 - val_scaled_adversarial_loss: 0.1882\n",
      "Epoch 9/1000\n",
      "12/12 [==============================] - 4s 372ms/step - loss: 0.6141 - sparse_categorical_crossentropy: 0.4454 - sparse_categorical_accuracy: 0.7935 - scaled_adversarial_loss: 0.1687 - val_loss: 0.5906 - val_sparse_categorical_crossentropy: 0.3866 - val_sparse_categorical_accuracy: 0.8301 - val_scaled_adversarial_loss: 0.2040\n",
      "Epoch 10/1000\n",
      "12/12 [==============================] - 4s 353ms/step - loss: 0.6301 - sparse_categorical_crossentropy: 0.4563 - sparse_categorical_accuracy: 0.7961 - scaled_adversarial_loss: 0.1738 - val_loss: 0.5832 - val_sparse_categorical_crossentropy: 0.3873 - val_sparse_categorical_accuracy: 0.8112 - val_scaled_adversarial_loss: 0.1960\n",
      "Epoch 11/1000\n",
      "12/12 [==============================] - 4s 350ms/step - loss: 0.6059 - sparse_categorical_crossentropy: 0.4380 - sparse_categorical_accuracy: 0.7996 - scaled_adversarial_loss: 0.1679 - val_loss: 0.5841 - val_sparse_categorical_crossentropy: 0.3842 - val_sparse_categorical_accuracy: 0.8308 - val_scaled_adversarial_loss: 0.1999\n",
      "Epoch 12/1000\n",
      "12/12 [==============================] - 4s 348ms/step - loss: 0.5984 - sparse_categorical_crossentropy: 0.4246 - sparse_categorical_accuracy: 0.8029 - scaled_adversarial_loss: 0.1737 - val_loss: 0.5785 - val_sparse_categorical_crossentropy: 0.3848 - val_sparse_categorical_accuracy: 0.8336 - val_scaled_adversarial_loss: 0.1937\n",
      "Epoch 13/1000\n",
      "12/12 [==============================] - 4s 360ms/step - loss: 0.5991 - sparse_categorical_crossentropy: 0.4206 - sparse_categorical_accuracy: 0.8134 - scaled_adversarial_loss: 0.1784 - val_loss: 0.5790 - val_sparse_categorical_crossentropy: 0.3882 - val_sparse_categorical_accuracy: 0.8413 - val_scaled_adversarial_loss: 0.1908\n",
      "Epoch 14/1000\n",
      "12/12 [==============================] - 4s 367ms/step - loss: 0.6031 - sparse_categorical_crossentropy: 0.4199 - sparse_categorical_accuracy: 0.8134 - scaled_adversarial_loss: 0.1832 - val_loss: 0.5806 - val_sparse_categorical_crossentropy: 0.3905 - val_sparse_categorical_accuracy: 0.8448 - val_scaled_adversarial_loss: 0.1901\n",
      "Epoch 15/1000\n",
      "12/12 [==============================] - 4s 371ms/step - loss: 0.5992 - sparse_categorical_crossentropy: 0.4186 - sparse_categorical_accuracy: 0.8201 - scaled_adversarial_loss: 0.1805 - val_loss: 0.5871 - val_sparse_categorical_crossentropy: 0.4095 - val_sparse_categorical_accuracy: 0.8329 - val_scaled_adversarial_loss: 0.1776\n",
      "Epoch 16/1000\n",
      "12/12 [==============================] - 4s 346ms/step - loss: 0.5895 - sparse_categorical_crossentropy: 0.4135 - sparse_categorical_accuracy: 0.8173 - scaled_adversarial_loss: 0.1760 - val_loss: 0.5738 - val_sparse_categorical_crossentropy: 0.3681 - val_sparse_categorical_accuracy: 0.8329 - val_scaled_adversarial_loss: 0.2056\n",
      "Epoch 17/1000\n",
      "12/12 [==============================] - 4s 338ms/step - loss: 0.6030 - sparse_categorical_crossentropy: 0.4114 - sparse_categorical_accuracy: 0.8248 - scaled_adversarial_loss: 0.1916 - val_loss: 0.5749 - val_sparse_categorical_crossentropy: 0.3779 - val_sparse_categorical_accuracy: 0.8245 - val_scaled_adversarial_loss: 0.1970\n",
      "Epoch 18/1000\n",
      "12/12 [==============================] - 4s 336ms/step - loss: 0.5825 - sparse_categorical_crossentropy: 0.4000 - sparse_categorical_accuracy: 0.8213 - scaled_adversarial_loss: 0.1825 - val_loss: 0.5731 - val_sparse_categorical_crossentropy: 0.3794 - val_sparse_categorical_accuracy: 0.8364 - val_scaled_adversarial_loss: 0.1937\n",
      "Epoch 19/1000\n",
      "12/12 [==============================] - 4s 347ms/step - loss: 0.5901 - sparse_categorical_crossentropy: 0.4021 - sparse_categorical_accuracy: 0.8250 - scaled_adversarial_loss: 0.1880 - val_loss: 0.5766 - val_sparse_categorical_crossentropy: 0.3882 - val_sparse_categorical_accuracy: 0.8196 - val_scaled_adversarial_loss: 0.1884\n",
      "Epoch 20/1000\n",
      "12/12 [==============================] - 4s 344ms/step - loss: 0.5897 - sparse_categorical_crossentropy: 0.4028 - sparse_categorical_accuracy: 0.8232 - scaled_adversarial_loss: 0.1869 - val_loss: 0.5826 - val_sparse_categorical_crossentropy: 0.3997 - val_sparse_categorical_accuracy: 0.8168 - val_scaled_adversarial_loss: 0.1829\n",
      "Epoch 21/1000\n",
      "12/12 [==============================] - 4s 334ms/step - loss: 0.5885 - sparse_categorical_crossentropy: 0.4033 - sparse_categorical_accuracy: 0.8225 - scaled_adversarial_loss: 0.1851 - val_loss: 0.5824 - val_sparse_categorical_crossentropy: 0.3980 - val_sparse_categorical_accuracy: 0.8105 - val_scaled_adversarial_loss: 0.1844\n",
      "Epoch 22/1000\n",
      "12/12 [==============================] - 4s 336ms/step - loss: 0.5958 - sparse_categorical_crossentropy: 0.4086 - sparse_categorical_accuracy: 0.8232 - scaled_adversarial_loss: 0.1872 - val_loss: 0.5781 - val_sparse_categorical_crossentropy: 0.3863 - val_sparse_categorical_accuracy: 0.8175 - val_scaled_adversarial_loss: 0.1918\n",
      "Epoch 23/1000\n",
      "12/12 [==============================] - 4s 334ms/step - loss: 0.5939 - sparse_categorical_crossentropy: 0.4052 - sparse_categorical_accuracy: 0.8155 - scaled_adversarial_loss: 0.1886 - val_loss: 0.5780 - val_sparse_categorical_crossentropy: 0.3957 - val_sparse_categorical_accuracy: 0.8308 - val_scaled_adversarial_loss: 0.1823\n",
      "Epoch 24/1000\n",
      "12/12 [==============================] - 4s 337ms/step - loss: 0.5954 - sparse_categorical_crossentropy: 0.4111 - sparse_categorical_accuracy: 0.8161 - scaled_adversarial_loss: 0.1843 - val_loss: 0.5746 - val_sparse_categorical_crossentropy: 0.3850 - val_sparse_categorical_accuracy: 0.8357 - val_scaled_adversarial_loss: 0.1896\n",
      "Epoch 25/1000\n",
      "12/12 [==============================] - 4s 334ms/step - loss: 0.5939 - sparse_categorical_crossentropy: 0.4130 - sparse_categorical_accuracy: 0.8115 - scaled_adversarial_loss: 0.1809 - val_loss: 0.5748 - val_sparse_categorical_crossentropy: 0.3702 - val_sparse_categorical_accuracy: 0.8594 - val_scaled_adversarial_loss: 0.2046\n",
      "Epoch 26/1000\n",
      "12/12 [==============================] - 4s 334ms/step - loss: 0.5814 - sparse_categorical_crossentropy: 0.3947 - sparse_categorical_accuracy: 0.8176 - scaled_adversarial_loss: 0.1867 - val_loss: 0.5714 - val_sparse_categorical_crossentropy: 0.3572 - val_sparse_categorical_accuracy: 0.8545 - val_scaled_adversarial_loss: 0.2143\n",
      "Epoch 27/1000\n",
      "12/12 [==============================] - 4s 332ms/step - loss: 0.5954 - sparse_categorical_crossentropy: 0.3986 - sparse_categorical_accuracy: 0.8346 - scaled_adversarial_loss: 0.1968 - val_loss: 0.5806 - val_sparse_categorical_crossentropy: 0.3966 - val_sparse_categorical_accuracy: 0.8140 - val_scaled_adversarial_loss: 0.1840\n",
      "Epoch 28/1000\n",
      "12/12 [==============================] - 4s 334ms/step - loss: 0.5814 - sparse_categorical_crossentropy: 0.3905 - sparse_categorical_accuracy: 0.8349 - scaled_adversarial_loss: 0.1909 - val_loss: 0.5735 - val_sparse_categorical_crossentropy: 0.3823 - val_sparse_categorical_accuracy: 0.8224 - val_scaled_adversarial_loss: 0.1912\n",
      "Epoch 29/1000\n",
      "12/12 [==============================] - 4s 334ms/step - loss: 0.5767 - sparse_categorical_crossentropy: 0.3846 - sparse_categorical_accuracy: 0.8325 - scaled_adversarial_loss: 0.1920 - val_loss: 0.5671 - val_sparse_categorical_crossentropy: 0.3647 - val_sparse_categorical_accuracy: 0.8378 - val_scaled_adversarial_loss: 0.2024\n",
      "Epoch 30/1000\n",
      "12/12 [==============================] - 4s 331ms/step - loss: 0.5778 - sparse_categorical_crossentropy: 0.3886 - sparse_categorical_accuracy: 0.8285 - scaled_adversarial_loss: 0.1891 - val_loss: 0.5679 - val_sparse_categorical_crossentropy: 0.3620 - val_sparse_categorical_accuracy: 0.8476 - val_scaled_adversarial_loss: 0.2059\n",
      "Epoch 31/1000\n",
      "12/12 [==============================] - 4s 334ms/step - loss: 0.5856 - sparse_categorical_crossentropy: 0.3909 - sparse_categorical_accuracy: 0.8286 - scaled_adversarial_loss: 0.1947 - val_loss: 0.5717 - val_sparse_categorical_crossentropy: 0.3762 - val_sparse_categorical_accuracy: 0.8238 - val_scaled_adversarial_loss: 0.1955\n",
      "Epoch 32/1000\n",
      "12/12 [==============================] - 4s 357ms/step - loss: 0.5804 - sparse_categorical_crossentropy: 0.3927 - sparse_categorical_accuracy: 0.8251 - scaled_adversarial_loss: 0.1877 - val_loss: 0.5701 - val_sparse_categorical_crossentropy: 0.3733 - val_sparse_categorical_accuracy: 0.8448 - val_scaled_adversarial_loss: 0.1968\n",
      "Epoch 33/1000\n",
      "12/12 [==============================] - 4s 352ms/step - loss: 0.5758 - sparse_categorical_crossentropy: 0.3845 - sparse_categorical_accuracy: 0.8349 - scaled_adversarial_loss: 0.1913 - val_loss: 0.5778 - val_sparse_categorical_crossentropy: 0.3700 - val_sparse_categorical_accuracy: 0.8168 - val_scaled_adversarial_loss: 0.2077\n",
      "Epoch 34/1000\n",
      "12/12 [==============================] - 4s 351ms/step - loss: 0.5898 - sparse_categorical_crossentropy: 0.3929 - sparse_categorical_accuracy: 0.8267 - scaled_adversarial_loss: 0.1970 - val_loss: 0.5685 - val_sparse_categorical_crossentropy: 0.3646 - val_sparse_categorical_accuracy: 0.8336 - val_scaled_adversarial_loss: 0.2040\n",
      "Epoch 35/1000\n",
      "12/12 [==============================] - 4s 348ms/step - loss: 0.5698 - sparse_categorical_crossentropy: 0.3820 - sparse_categorical_accuracy: 0.8304 - scaled_adversarial_loss: 0.1878 - val_loss: 0.5713 - val_sparse_categorical_crossentropy: 0.3563 - val_sparse_categorical_accuracy: 0.8343 - val_scaled_adversarial_loss: 0.2150\n",
      "Epoch 36/1000\n",
      "12/12 [==============================] - 4s 353ms/step - loss: 0.5743 - sparse_categorical_crossentropy: 0.3821 - sparse_categorical_accuracy: 0.8304 - scaled_adversarial_loss: 0.1922 - val_loss: 0.5794 - val_sparse_categorical_crossentropy: 0.3380 - val_sparse_categorical_accuracy: 0.8629 - val_scaled_adversarial_loss: 0.2414\n",
      "Epoch 37/1000\n",
      "12/12 [==============================] - 4s 358ms/step - loss: 0.5919 - sparse_categorical_crossentropy: 0.3947 - sparse_categorical_accuracy: 0.8258 - scaled_adversarial_loss: 0.1972 - val_loss: 0.5703 - val_sparse_categorical_crossentropy: 0.3746 - val_sparse_categorical_accuracy: 0.8399 - val_scaled_adversarial_loss: 0.1957\n",
      "Epoch 38/1000\n",
      "12/12 [==============================] - 4s 351ms/step - loss: 0.5782 - sparse_categorical_crossentropy: 0.3887 - sparse_categorical_accuracy: 0.8334 - scaled_adversarial_loss: 0.1895 - val_loss: 0.5723 - val_sparse_categorical_crossentropy: 0.3789 - val_sparse_categorical_accuracy: 0.8476 - val_scaled_adversarial_loss: 0.1934\n",
      "Epoch 39/1000\n",
      "12/12 [==============================] - 4s 339ms/step - loss: 0.5795 - sparse_categorical_crossentropy: 0.3908 - sparse_categorical_accuracy: 0.8230 - scaled_adversarial_loss: 0.1886 - val_loss: 0.5701 - val_sparse_categorical_crossentropy: 0.3665 - val_sparse_categorical_accuracy: 0.8301 - val_scaled_adversarial_loss: 0.2036\n",
      "Epoch 40/1000\n",
      "12/12 [==============================] - 4s 339ms/step - loss: 0.5734 - sparse_categorical_crossentropy: 0.3796 - sparse_categorical_accuracy: 0.8379 - scaled_adversarial_loss: 0.1938 - val_loss: 0.5859 - val_sparse_categorical_crossentropy: 0.3521 - val_sparse_categorical_accuracy: 0.8371 - val_scaled_adversarial_loss: 0.2337\n",
      "Epoch 41/1000\n",
      "12/12 [==============================] - 4s 351ms/step - loss: 0.5898 - sparse_categorical_crossentropy: 0.3911 - sparse_categorical_accuracy: 0.8311 - scaled_adversarial_loss: 0.1987 - val_loss: 0.5681 - val_sparse_categorical_crossentropy: 0.3566 - val_sparse_categorical_accuracy: 0.8378 - val_scaled_adversarial_loss: 0.2116\n",
      "Epoch 42/1000\n",
      "12/12 [==============================] - 4s 371ms/step - loss: 0.5721 - sparse_categorical_crossentropy: 0.3786 - sparse_categorical_accuracy: 0.8369 - scaled_adversarial_loss: 0.1935 - val_loss: 0.5669 - val_sparse_categorical_crossentropy: 0.3605 - val_sparse_categorical_accuracy: 0.8322 - val_scaled_adversarial_loss: 0.2064\n",
      "Epoch 43/1000\n",
      "12/12 [==============================] - 5s 376ms/step - loss: 0.5739 - sparse_categorical_crossentropy: 0.3803 - sparse_categorical_accuracy: 0.8390 - scaled_adversarial_loss: 0.1936 - val_loss: 0.5698 - val_sparse_categorical_crossentropy: 0.3673 - val_sparse_categorical_accuracy: 0.8357 - val_scaled_adversarial_loss: 0.2024\n",
      "Epoch 44/1000\n",
      "12/12 [==============================] - 4s 350ms/step - loss: 0.5727 - sparse_categorical_crossentropy: 0.3797 - sparse_categorical_accuracy: 0.8344 - scaled_adversarial_loss: 0.1929 - val_loss: 0.5707 - val_sparse_categorical_crossentropy: 0.3505 - val_sparse_categorical_accuracy: 0.8441 - val_scaled_adversarial_loss: 0.2203\n",
      "Epoch 45/1000\n",
      "12/12 [==============================] - 4s 348ms/step - loss: 0.5713 - sparse_categorical_crossentropy: 0.3783 - sparse_categorical_accuracy: 0.8355 - scaled_adversarial_loss: 0.1930 - val_loss: 0.5731 - val_sparse_categorical_crossentropy: 0.3556 - val_sparse_categorical_accuracy: 0.8280 - val_scaled_adversarial_loss: 0.2175\n",
      "Epoch 46/1000\n",
      "12/12 [==============================] - 4s 370ms/step - loss: 0.5866 - sparse_categorical_crossentropy: 0.3860 - sparse_categorical_accuracy: 0.8321 - scaled_adversarial_loss: 0.2006 - val_loss: 0.5740 - val_sparse_categorical_crossentropy: 0.3727 - val_sparse_categorical_accuracy: 0.8161 - val_scaled_adversarial_loss: 0.2014\n",
      "Epoch 47/1000\n",
      "12/12 [==============================] - 4s 351ms/step - loss: 0.5827 - sparse_categorical_crossentropy: 0.3912 - sparse_categorical_accuracy: 0.8241 - scaled_adversarial_loss: 0.1914 - val_loss: 0.5680 - val_sparse_categorical_crossentropy: 0.3689 - val_sparse_categorical_accuracy: 0.8476 - val_scaled_adversarial_loss: 0.1991\n",
      "Epoch 48/1000\n",
      "12/12 [==============================] - 4s 353ms/step - loss: 0.5753 - sparse_categorical_crossentropy: 0.3786 - sparse_categorical_accuracy: 0.8412 - scaled_adversarial_loss: 0.1967 - val_loss: 0.5686 - val_sparse_categorical_crossentropy: 0.3708 - val_sparse_categorical_accuracy: 0.8413 - val_scaled_adversarial_loss: 0.1978\n",
      "Epoch 49/1000\n",
      "12/12 [==============================] - 4s 348ms/step - loss: 0.5779 - sparse_categorical_crossentropy: 0.3812 - sparse_categorical_accuracy: 0.8307 - scaled_adversarial_loss: 0.1968 - val_loss: 0.5751 - val_sparse_categorical_crossentropy: 0.3891 - val_sparse_categorical_accuracy: 0.8427 - val_scaled_adversarial_loss: 0.1860\n",
      "Epoch 50/1000\n",
      "12/12 [==============================] - 4s 354ms/step - loss: 0.5751 - sparse_categorical_crossentropy: 0.3835 - sparse_categorical_accuracy: 0.8356 - scaled_adversarial_loss: 0.1916 - val_loss: 0.5680 - val_sparse_categorical_crossentropy: 0.3694 - val_sparse_categorical_accuracy: 0.8455 - val_scaled_adversarial_loss: 0.1986\n",
      "Epoch 51/1000\n",
      "12/12 [==============================] - 4s 354ms/step - loss: 0.5765 - sparse_categorical_crossentropy: 0.3769 - sparse_categorical_accuracy: 0.8323 - scaled_adversarial_loss: 0.1995 - val_loss: 0.5748 - val_sparse_categorical_crossentropy: 0.3846 - val_sparse_categorical_accuracy: 0.8510 - val_scaled_adversarial_loss: 0.1902\n",
      "Epoch 52/1000\n",
      "12/12 [==============================] - 4s 354ms/step - loss: 0.5754 - sparse_categorical_crossentropy: 0.3860 - sparse_categorical_accuracy: 0.8241 - scaled_adversarial_loss: 0.1894 - val_loss: 0.5750 - val_sparse_categorical_crossentropy: 0.3673 - val_sparse_categorical_accuracy: 0.8657 - val_scaled_adversarial_loss: 0.2077\n",
      "Epoch 53/1000\n",
      "12/12 [==============================] - 4s 339ms/step - loss: 0.5833 - sparse_categorical_crossentropy: 0.3881 - sparse_categorical_accuracy: 0.8307 - scaled_adversarial_loss: 0.1952 - val_loss: 0.5706 - val_sparse_categorical_crossentropy: 0.3673 - val_sparse_categorical_accuracy: 0.8594 - val_scaled_adversarial_loss: 0.2033\n",
      "Epoch 54/1000\n",
      "12/12 [==============================] - 4s 328ms/step - loss: 0.5697 - sparse_categorical_crossentropy: 0.3767 - sparse_categorical_accuracy: 0.8372 - scaled_adversarial_loss: 0.1930 - val_loss: 0.5712 - val_sparse_categorical_crossentropy: 0.3458 - val_sparse_categorical_accuracy: 0.8462 - val_scaled_adversarial_loss: 0.2254\n",
      "Epoch 55/1000\n",
      "12/12 [==============================] - 4s 338ms/step - loss: 0.5763 - sparse_categorical_crossentropy: 0.3751 - sparse_categorical_accuracy: 0.8428 - scaled_adversarial_loss: 0.2012 - val_loss: 0.5712 - val_sparse_categorical_crossentropy: 0.3736 - val_sparse_categorical_accuracy: 0.8280 - val_scaled_adversarial_loss: 0.1976\n",
      "Epoch 56/1000\n",
      "12/12 [==============================] - 4s 369ms/step - loss: 0.5659 - sparse_categorical_crossentropy: 0.3686 - sparse_categorical_accuracy: 0.8414 - scaled_adversarial_loss: 0.1973 - val_loss: 0.5724 - val_sparse_categorical_crossentropy: 0.3728 - val_sparse_categorical_accuracy: 0.8280 - val_scaled_adversarial_loss: 0.1997\n",
      "Epoch 57/1000\n",
      "12/12 [==============================] - 4s 347ms/step - loss: 0.5746 - sparse_categorical_crossentropy: 0.3767 - sparse_categorical_accuracy: 0.8428 - scaled_adversarial_loss: 0.1980 - val_loss: 0.5749 - val_sparse_categorical_crossentropy: 0.3876 - val_sparse_categorical_accuracy: 0.8280 - val_scaled_adversarial_loss: 0.1873\n",
      "Epoch 58/1000\n",
      "12/12 [==============================] - 4s 348ms/step - loss: 0.5700 - sparse_categorical_crossentropy: 0.3758 - sparse_categorical_accuracy: 0.8412 - scaled_adversarial_loss: 0.1942 - val_loss: 0.5641 - val_sparse_categorical_crossentropy: 0.3507 - val_sparse_categorical_accuracy: 0.8371 - val_scaled_adversarial_loss: 0.2134\n",
      "Epoch 59/1000\n",
      "12/12 [==============================] - 4s 342ms/step - loss: 0.5592 - sparse_categorical_crossentropy: 0.3625 - sparse_categorical_accuracy: 0.8467 - scaled_adversarial_loss: 0.1967 - val_loss: 0.5718 - val_sparse_categorical_crossentropy: 0.3286 - val_sparse_categorical_accuracy: 0.8524 - val_scaled_adversarial_loss: 0.2433\n",
      "Epoch 60/1000\n",
      "12/12 [==============================] - 4s 377ms/step - loss: 0.5736 - sparse_categorical_crossentropy: 0.3697 - sparse_categorical_accuracy: 0.8501 - scaled_adversarial_loss: 0.2039 - val_loss: 0.5691 - val_sparse_categorical_crossentropy: 0.3630 - val_sparse_categorical_accuracy: 0.8329 - val_scaled_adversarial_loss: 0.2060\n",
      "Epoch 61/1000\n",
      "12/12 [==============================] - 4s 369ms/step - loss: 0.5650 - sparse_categorical_crossentropy: 0.3664 - sparse_categorical_accuracy: 0.8491 - scaled_adversarial_loss: 0.1986 - val_loss: 0.5601 - val_sparse_categorical_crossentropy: 0.3481 - val_sparse_categorical_accuracy: 0.8434 - val_scaled_adversarial_loss: 0.2120\n",
      "Epoch 62/1000\n",
      "12/12 [==============================] - 4s 356ms/step - loss: 0.5648 - sparse_categorical_crossentropy: 0.3621 - sparse_categorical_accuracy: 0.8501 - scaled_adversarial_loss: 0.2027 - val_loss: 0.5582 - val_sparse_categorical_crossentropy: 0.3354 - val_sparse_categorical_accuracy: 0.8594 - val_scaled_adversarial_loss: 0.2228\n",
      "Epoch 63/1000\n",
      "12/12 [==============================] - 4s 342ms/step - loss: 0.5606 - sparse_categorical_crossentropy: 0.3546 - sparse_categorical_accuracy: 0.8554 - scaled_adversarial_loss: 0.2060 - val_loss: 0.5568 - val_sparse_categorical_crossentropy: 0.3473 - val_sparse_categorical_accuracy: 0.8664 - val_scaled_adversarial_loss: 0.2095\n",
      "Epoch 64/1000\n",
      "12/12 [==============================] - 4s 334ms/step - loss: 0.5661 - sparse_categorical_crossentropy: 0.3632 - sparse_categorical_accuracy: 0.8571 - scaled_adversarial_loss: 0.2030 - val_loss: 0.5589 - val_sparse_categorical_crossentropy: 0.3524 - val_sparse_categorical_accuracy: 0.8755 - val_scaled_adversarial_loss: 0.2065\n",
      "Epoch 65/1000\n",
      "12/12 [==============================] - 4s 333ms/step - loss: 0.5669 - sparse_categorical_crossentropy: 0.3664 - sparse_categorical_accuracy: 0.8468 - scaled_adversarial_loss: 0.2005 - val_loss: 0.5596 - val_sparse_categorical_crossentropy: 0.3509 - val_sparse_categorical_accuracy: 0.8692 - val_scaled_adversarial_loss: 0.2087\n",
      "Epoch 66/1000\n",
      "12/12 [==============================] - 4s 338ms/step - loss: 0.5581 - sparse_categorical_crossentropy: 0.3566 - sparse_categorical_accuracy: 0.8584 - scaled_adversarial_loss: 0.2015 - val_loss: 0.5539 - val_sparse_categorical_crossentropy: 0.3441 - val_sparse_categorical_accuracy: 0.8643 - val_scaled_adversarial_loss: 0.2098\n",
      "Epoch 67/1000\n",
      "12/12 [==============================] - 4s 336ms/step - loss: 0.5627 - sparse_categorical_crossentropy: 0.3611 - sparse_categorical_accuracy: 0.8580 - scaled_adversarial_loss: 0.2016 - val_loss: 0.5593 - val_sparse_categorical_crossentropy: 0.3585 - val_sparse_categorical_accuracy: 0.8734 - val_scaled_adversarial_loss: 0.2008\n",
      "Epoch 68/1000\n",
      "12/12 [==============================] - 4s 333ms/step - loss: 0.5540 - sparse_categorical_crossentropy: 0.3541 - sparse_categorical_accuracy: 0.8585 - scaled_adversarial_loss: 0.1999 - val_loss: 0.5529 - val_sparse_categorical_crossentropy: 0.3299 - val_sparse_categorical_accuracy: 0.8629 - val_scaled_adversarial_loss: 0.2230\n",
      "Epoch 69/1000\n",
      "12/12 [==============================] - 4s 333ms/step - loss: 0.5526 - sparse_categorical_crossentropy: 0.3496 - sparse_categorical_accuracy: 0.8587 - scaled_adversarial_loss: 0.2030 - val_loss: 0.5538 - val_sparse_categorical_crossentropy: 0.3285 - val_sparse_categorical_accuracy: 0.8531 - val_scaled_adversarial_loss: 0.2253\n",
      "Epoch 70/1000\n",
      "12/12 [==============================] - 4s 341ms/step - loss: 0.5433 - sparse_categorical_crossentropy: 0.3429 - sparse_categorical_accuracy: 0.8673 - scaled_adversarial_loss: 0.2004 - val_loss: 0.5439 - val_sparse_categorical_crossentropy: 0.3128 - val_sparse_categorical_accuracy: 0.8622 - val_scaled_adversarial_loss: 0.2311\n",
      "Epoch 71/1000\n",
      "12/12 [==============================] - 4s 339ms/step - loss: 0.5481 - sparse_categorical_crossentropy: 0.3430 - sparse_categorical_accuracy: 0.8696 - scaled_adversarial_loss: 0.2051 - val_loss: 0.5227 - val_sparse_categorical_crossentropy: 0.3276 - val_sparse_categorical_accuracy: 0.8692 - val_scaled_adversarial_loss: 0.1950\n",
      "Epoch 72/1000\n",
      "12/12 [==============================] - 4s 338ms/step - loss: 0.5312 - sparse_categorical_crossentropy: 0.3332 - sparse_categorical_accuracy: 0.8697 - scaled_adversarial_loss: 0.1980 - val_loss: 0.5349 - val_sparse_categorical_crossentropy: 0.2917 - val_sparse_categorical_accuracy: 0.8895 - val_scaled_adversarial_loss: 0.2432\n",
      "Epoch 73/1000\n",
      "12/12 [==============================] - 4s 335ms/step - loss: 0.5293 - sparse_categorical_crossentropy: 0.3324 - sparse_categorical_accuracy: 0.8729 - scaled_adversarial_loss: 0.1969 - val_loss: 0.5191 - val_sparse_categorical_crossentropy: 0.3147 - val_sparse_categorical_accuracy: 0.9014 - val_scaled_adversarial_loss: 0.2044\n",
      "Epoch 74/1000\n",
      "12/12 [==============================] - 4s 338ms/step - loss: 0.5228 - sparse_categorical_crossentropy: 0.3226 - sparse_categorical_accuracy: 0.8776 - scaled_adversarial_loss: 0.2002 - val_loss: 0.4906 - val_sparse_categorical_crossentropy: 0.3229 - val_sparse_categorical_accuracy: 0.8923 - val_scaled_adversarial_loss: 0.1677\n",
      "Epoch 75/1000\n",
      "12/12 [==============================] - 4s 336ms/step - loss: 0.5100 - sparse_categorical_crossentropy: 0.3245 - sparse_categorical_accuracy: 0.8830 - scaled_adversarial_loss: 0.1854 - val_loss: 0.4869 - val_sparse_categorical_crossentropy: 0.2938 - val_sparse_categorical_accuracy: 0.9035 - val_scaled_adversarial_loss: 0.1931\n",
      "Epoch 76/1000\n",
      "12/12 [==============================] - 4s 334ms/step - loss: 0.4952 - sparse_categorical_crossentropy: 0.3121 - sparse_categorical_accuracy: 0.8860 - scaled_adversarial_loss: 0.1831 - val_loss: 0.4327 - val_sparse_categorical_crossentropy: 0.2804 - val_sparse_categorical_accuracy: 0.9154 - val_scaled_adversarial_loss: 0.1523\n",
      "Epoch 77/1000\n",
      "12/12 [==============================] - 4s 340ms/step - loss: 0.4609 - sparse_categorical_crossentropy: 0.2933 - sparse_categorical_accuracy: 0.8974 - scaled_adversarial_loss: 0.1676 - val_loss: 0.3940 - val_sparse_categorical_crossentropy: 0.2465 - val_sparse_categorical_accuracy: 0.9161 - val_scaled_adversarial_loss: 0.1475\n",
      "Epoch 78/1000\n",
      "12/12 [==============================] - 4s 338ms/step - loss: 0.4288 - sparse_categorical_crossentropy: 0.2768 - sparse_categorical_accuracy: 0.8995 - scaled_adversarial_loss: 0.1520 - val_loss: 0.3554 - val_sparse_categorical_crossentropy: 0.2436 - val_sparse_categorical_accuracy: 0.9196 - val_scaled_adversarial_loss: 0.1118\n",
      "Epoch 79/1000\n",
      "12/12 [==============================] - 4s 335ms/step - loss: 0.4292 - sparse_categorical_crossentropy: 0.2790 - sparse_categorical_accuracy: 0.9023 - scaled_adversarial_loss: 0.1502 - val_loss: 0.3537 - val_sparse_categorical_crossentropy: 0.2204 - val_sparse_categorical_accuracy: 0.9287 - val_scaled_adversarial_loss: 0.1333\n",
      "Epoch 80/1000\n",
      "12/12 [==============================] - 4s 341ms/step - loss: 0.4201 - sparse_categorical_crossentropy: 0.2666 - sparse_categorical_accuracy: 0.9119 - scaled_adversarial_loss: 0.1535 - val_loss: 0.3481 - val_sparse_categorical_crossentropy: 0.2135 - val_sparse_categorical_accuracy: 0.9294 - val_scaled_adversarial_loss: 0.1346\n",
      "Epoch 81/1000\n",
      "12/12 [==============================] - 4s 345ms/step - loss: 0.3885 - sparse_categorical_crossentropy: 0.2551 - sparse_categorical_accuracy: 0.9178 - scaled_adversarial_loss: 0.1335 - val_loss: 0.3285 - val_sparse_categorical_crossentropy: 0.1976 - val_sparse_categorical_accuracy: 0.9399 - val_scaled_adversarial_loss: 0.1309\n",
      "Epoch 82/1000\n",
      "12/12 [==============================] - 4s 341ms/step - loss: 0.3771 - sparse_categorical_crossentropy: 0.2441 - sparse_categorical_accuracy: 0.9157 - scaled_adversarial_loss: 0.1330 - val_loss: 0.3006 - val_sparse_categorical_crossentropy: 0.1890 - val_sparse_categorical_accuracy: 0.9399 - val_scaled_adversarial_loss: 0.1117\n",
      "Epoch 83/1000\n",
      "12/12 [==============================] - 4s 337ms/step - loss: 0.3701 - sparse_categorical_crossentropy: 0.2309 - sparse_categorical_accuracy: 0.9187 - scaled_adversarial_loss: 0.1392 - val_loss: 0.3102 - val_sparse_categorical_crossentropy: 0.1829 - val_sparse_categorical_accuracy: 0.9399 - val_scaled_adversarial_loss: 0.1273\n",
      "Epoch 84/1000\n",
      "12/12 [==============================] - 4s 363ms/step - loss: 0.3411 - sparse_categorical_crossentropy: 0.2164 - sparse_categorical_accuracy: 0.9241 - scaled_adversarial_loss: 0.1247 - val_loss: 0.2619 - val_sparse_categorical_crossentropy: 0.1931 - val_sparse_categorical_accuracy: 0.9182 - val_scaled_adversarial_loss: 0.0688\n",
      "Epoch 85/1000\n",
      "12/12 [==============================] - 4s 341ms/step - loss: 0.3390 - sparse_categorical_crossentropy: 0.2251 - sparse_categorical_accuracy: 0.9201 - scaled_adversarial_loss: 0.1139 - val_loss: 0.2519 - val_sparse_categorical_crossentropy: 0.1718 - val_sparse_categorical_accuracy: 0.9462 - val_scaled_adversarial_loss: 0.0800\n",
      "Epoch 86/1000\n",
      "12/12 [==============================] - 4s 370ms/step - loss: 0.3284 - sparse_categorical_crossentropy: 0.2191 - sparse_categorical_accuracy: 0.9276 - scaled_adversarial_loss: 0.1093 - val_loss: 0.2500 - val_sparse_categorical_crossentropy: 0.1673 - val_sparse_categorical_accuracy: 0.9503 - val_scaled_adversarial_loss: 0.0827\n",
      "Epoch 87/1000\n",
      "12/12 [==============================] - 4s 351ms/step - loss: 0.3082 - sparse_categorical_crossentropy: 0.2054 - sparse_categorical_accuracy: 0.9315 - scaled_adversarial_loss: 0.1028 - val_loss: 0.2286 - val_sparse_categorical_crossentropy: 0.1588 - val_sparse_categorical_accuracy: 0.9538 - val_scaled_adversarial_loss: 0.0698\n",
      "Epoch 88/1000\n",
      "12/12 [==============================] - 4s 351ms/step - loss: 0.3145 - sparse_categorical_crossentropy: 0.2060 - sparse_categorical_accuracy: 0.9297 - scaled_adversarial_loss: 0.1085 - val_loss: 0.2383 - val_sparse_categorical_crossentropy: 0.1531 - val_sparse_categorical_accuracy: 0.9545 - val_scaled_adversarial_loss: 0.0852\n",
      "Epoch 89/1000\n",
      "12/12 [==============================] - 4s 354ms/step - loss: 0.2946 - sparse_categorical_crossentropy: 0.1945 - sparse_categorical_accuracy: 0.9351 - scaled_adversarial_loss: 0.1001 - val_loss: 0.2361 - val_sparse_categorical_crossentropy: 0.1587 - val_sparse_categorical_accuracy: 0.9483 - val_scaled_adversarial_loss: 0.0774\n",
      "Epoch 90/1000\n",
      "12/12 [==============================] - 4s 363ms/step - loss: 0.2859 - sparse_categorical_crossentropy: 0.1939 - sparse_categorical_accuracy: 0.9371 - scaled_adversarial_loss: 0.0920 - val_loss: 0.2253 - val_sparse_categorical_crossentropy: 0.1548 - val_sparse_categorical_accuracy: 0.9497 - val_scaled_adversarial_loss: 0.0704\n",
      "Epoch 91/1000\n",
      "12/12 [==============================] - 4s 367ms/step - loss: 0.2843 - sparse_categorical_crossentropy: 0.1907 - sparse_categorical_accuracy: 0.9385 - scaled_adversarial_loss: 0.0936 - val_loss: 0.2234 - val_sparse_categorical_crossentropy: 0.1441 - val_sparse_categorical_accuracy: 0.9566 - val_scaled_adversarial_loss: 0.0792\n",
      "Epoch 92/1000\n",
      "12/12 [==============================] - 4s 344ms/step - loss: 0.2675 - sparse_categorical_crossentropy: 0.1852 - sparse_categorical_accuracy: 0.9404 - scaled_adversarial_loss: 0.0823 - val_loss: 0.2090 - val_sparse_categorical_crossentropy: 0.1485 - val_sparse_categorical_accuracy: 0.9510 - val_scaled_adversarial_loss: 0.0605\n",
      "Epoch 93/1000\n",
      "12/12 [==============================] - 4s 345ms/step - loss: 0.2711 - sparse_categorical_crossentropy: 0.1875 - sparse_categorical_accuracy: 0.9362 - scaled_adversarial_loss: 0.0836 - val_loss: 0.2061 - val_sparse_categorical_crossentropy: 0.1408 - val_sparse_categorical_accuracy: 0.9545 - val_scaled_adversarial_loss: 0.0654\n",
      "Epoch 94/1000\n",
      "12/12 [==============================] - 4s 339ms/step - loss: 0.2874 - sparse_categorical_crossentropy: 0.1894 - sparse_categorical_accuracy: 0.9341 - scaled_adversarial_loss: 0.0980 - val_loss: 0.2434 - val_sparse_categorical_crossentropy: 0.1484 - val_sparse_categorical_accuracy: 0.9503 - val_scaled_adversarial_loss: 0.0950\n",
      "Epoch 95/1000\n",
      "12/12 [==============================] - 4s 335ms/step - loss: 0.2759 - sparse_categorical_crossentropy: 0.1861 - sparse_categorical_accuracy: 0.9358 - scaled_adversarial_loss: 0.0898 - val_loss: 0.2046 - val_sparse_categorical_crossentropy: 0.1408 - val_sparse_categorical_accuracy: 0.9559 - val_scaled_adversarial_loss: 0.0638\n",
      "Epoch 96/1000\n",
      "12/12 [==============================] - 4s 365ms/step - loss: 0.2613 - sparse_categorical_crossentropy: 0.1769 - sparse_categorical_accuracy: 0.9428 - scaled_adversarial_loss: 0.0844 - val_loss: 0.2102 - val_sparse_categorical_crossentropy: 0.1482 - val_sparse_categorical_accuracy: 0.9524 - val_scaled_adversarial_loss: 0.0620\n",
      "Epoch 97/1000\n",
      "12/12 [==============================] - 4s 341ms/step - loss: 0.2641 - sparse_categorical_crossentropy: 0.1802 - sparse_categorical_accuracy: 0.9453 - scaled_adversarial_loss: 0.0839 - val_loss: 0.1935 - val_sparse_categorical_crossentropy: 0.1462 - val_sparse_categorical_accuracy: 0.9531 - val_scaled_adversarial_loss: 0.0473\n",
      "Epoch 98/1000\n",
      "12/12 [==============================] - 4s 345ms/step - loss: 0.2561 - sparse_categorical_crossentropy: 0.1758 - sparse_categorical_accuracy: 0.9411 - scaled_adversarial_loss: 0.0803 - val_loss: 0.2093 - val_sparse_categorical_crossentropy: 0.1553 - val_sparse_categorical_accuracy: 0.9510 - val_scaled_adversarial_loss: 0.0540\n",
      "Epoch 99/1000\n",
      "12/12 [==============================] - 4s 363ms/step - loss: 0.2508 - sparse_categorical_crossentropy: 0.1722 - sparse_categorical_accuracy: 0.9435 - scaled_adversarial_loss: 0.0786 - val_loss: 0.2123 - val_sparse_categorical_crossentropy: 0.1442 - val_sparse_categorical_accuracy: 0.9531 - val_scaled_adversarial_loss: 0.0681\n",
      "Epoch 100/1000\n",
      "12/12 [==============================] - 4s 340ms/step - loss: 0.2515 - sparse_categorical_crossentropy: 0.1666 - sparse_categorical_accuracy: 0.9398 - scaled_adversarial_loss: 0.0849 - val_loss: 0.1923 - val_sparse_categorical_crossentropy: 0.1340 - val_sparse_categorical_accuracy: 0.9552 - val_scaled_adversarial_loss: 0.0583\n",
      "Epoch 101/1000\n",
      "12/12 [==============================] - 4s 334ms/step - loss: 0.2505 - sparse_categorical_crossentropy: 0.1665 - sparse_categorical_accuracy: 0.9477 - scaled_adversarial_loss: 0.0840 - val_loss: 0.1824 - val_sparse_categorical_crossentropy: 0.1292 - val_sparse_categorical_accuracy: 0.9573 - val_scaled_adversarial_loss: 0.0532\n",
      "Epoch 102/1000\n",
      "12/12 [==============================] - 4s 333ms/step - loss: 0.2485 - sparse_categorical_crossentropy: 0.1616 - sparse_categorical_accuracy: 0.9467 - scaled_adversarial_loss: 0.0868 - val_loss: 0.1900 - val_sparse_categorical_crossentropy: 0.1272 - val_sparse_categorical_accuracy: 0.9524 - val_scaled_adversarial_loss: 0.0628\n",
      "Epoch 103/1000\n",
      "12/12 [==============================] - 4s 337ms/step - loss: 0.2597 - sparse_categorical_crossentropy: 0.1738 - sparse_categorical_accuracy: 0.9423 - scaled_adversarial_loss: 0.0859 - val_loss: 0.1930 - val_sparse_categorical_crossentropy: 0.1293 - val_sparse_categorical_accuracy: 0.9566 - val_scaled_adversarial_loss: 0.0638\n",
      "Epoch 104/1000\n",
      "12/12 [==============================] - 4s 335ms/step - loss: 0.2594 - sparse_categorical_crossentropy: 0.1700 - sparse_categorical_accuracy: 0.9379 - scaled_adversarial_loss: 0.0895 - val_loss: 0.1790 - val_sparse_categorical_crossentropy: 0.1276 - val_sparse_categorical_accuracy: 0.9559 - val_scaled_adversarial_loss: 0.0514\n",
      "Epoch 105/1000\n",
      "12/12 [==============================] - 4s 340ms/step - loss: 0.2489 - sparse_categorical_crossentropy: 0.1676 - sparse_categorical_accuracy: 0.9446 - scaled_adversarial_loss: 0.0813 - val_loss: 0.1834 - val_sparse_categorical_crossentropy: 0.1252 - val_sparse_categorical_accuracy: 0.9580 - val_scaled_adversarial_loss: 0.0582\n",
      "Epoch 106/1000\n",
      "12/12 [==============================] - 4s 345ms/step - loss: 0.2468 - sparse_categorical_crossentropy: 0.1617 - sparse_categorical_accuracy: 0.9467 - scaled_adversarial_loss: 0.0851 - val_loss: 0.1875 - val_sparse_categorical_crossentropy: 0.1290 - val_sparse_categorical_accuracy: 0.9552 - val_scaled_adversarial_loss: 0.0585\n",
      "Epoch 107/1000\n",
      "12/12 [==============================] - 4s 334ms/step - loss: 0.2592 - sparse_categorical_crossentropy: 0.1658 - sparse_categorical_accuracy: 0.9486 - scaled_adversarial_loss: 0.0934 - val_loss: 0.1871 - val_sparse_categorical_crossentropy: 0.1279 - val_sparse_categorical_accuracy: 0.9573 - val_scaled_adversarial_loss: 0.0593\n",
      "Epoch 108/1000\n",
      "12/12 [==============================] - 4s 336ms/step - loss: 0.2372 - sparse_categorical_crossentropy: 0.1541 - sparse_categorical_accuracy: 0.9474 - scaled_adversarial_loss: 0.0831 - val_loss: 0.1819 - val_sparse_categorical_crossentropy: 0.1214 - val_sparse_categorical_accuracy: 0.9608 - val_scaled_adversarial_loss: 0.0605\n",
      "Epoch 109/1000\n",
      "12/12 [==============================] - 4s 344ms/step - loss: 0.2556 - sparse_categorical_crossentropy: 0.1640 - sparse_categorical_accuracy: 0.9493 - scaled_adversarial_loss: 0.0916 - val_loss: 0.1791 - val_sparse_categorical_crossentropy: 0.1174 - val_sparse_categorical_accuracy: 0.9608 - val_scaled_adversarial_loss: 0.0616\n",
      "Epoch 110/1000\n",
      "12/12 [==============================] - 4s 336ms/step - loss: 0.2318 - sparse_categorical_crossentropy: 0.1505 - sparse_categorical_accuracy: 0.9491 - scaled_adversarial_loss: 0.0813 - val_loss: 0.1835 - val_sparse_categorical_crossentropy: 0.1124 - val_sparse_categorical_accuracy: 0.9636 - val_scaled_adversarial_loss: 0.0711\n",
      "Epoch 111/1000\n",
      "12/12 [==============================] - 4s 334ms/step - loss: 0.2406 - sparse_categorical_crossentropy: 0.1535 - sparse_categorical_accuracy: 0.9502 - scaled_adversarial_loss: 0.0872 - val_loss: 0.1911 - val_sparse_categorical_crossentropy: 0.1306 - val_sparse_categorical_accuracy: 0.9490 - val_scaled_adversarial_loss: 0.0606\n",
      "Epoch 112/1000\n",
      "12/12 [==============================] - 4s 336ms/step - loss: 0.2561 - sparse_categorical_crossentropy: 0.1638 - sparse_categorical_accuracy: 0.9405 - scaled_adversarial_loss: 0.0923 - val_loss: 0.2164 - val_sparse_categorical_crossentropy: 0.1316 - val_sparse_categorical_accuracy: 0.9566 - val_scaled_adversarial_loss: 0.0848\n",
      "Epoch 113/1000\n",
      "12/12 [==============================] - 4s 338ms/step - loss: 0.2416 - sparse_categorical_crossentropy: 0.1547 - sparse_categorical_accuracy: 0.9440 - scaled_adversarial_loss: 0.0869 - val_loss: 0.1859 - val_sparse_categorical_crossentropy: 0.1179 - val_sparse_categorical_accuracy: 0.9559 - val_scaled_adversarial_loss: 0.0680\n",
      "Epoch 114/1000\n",
      "12/12 [==============================] - 4s 334ms/step - loss: 0.2502 - sparse_categorical_crossentropy: 0.1565 - sparse_categorical_accuracy: 0.9472 - scaled_adversarial_loss: 0.0937 - val_loss: 0.2005 - val_sparse_categorical_crossentropy: 0.1154 - val_sparse_categorical_accuracy: 0.9601 - val_scaled_adversarial_loss: 0.0851\n",
      "Epoch 115/1000\n",
      "12/12 [==============================] - 4s 338ms/step - loss: 0.2501 - sparse_categorical_crossentropy: 0.1581 - sparse_categorical_accuracy: 0.9500 - scaled_adversarial_loss: 0.0920 - val_loss: 0.1966 - val_sparse_categorical_crossentropy: 0.1143 - val_sparse_categorical_accuracy: 0.9629 - val_scaled_adversarial_loss: 0.0823\n",
      "Epoch 116/1000\n",
      "12/12 [==============================] - 4s 332ms/step - loss: 0.2309 - sparse_categorical_crossentropy: 0.1449 - sparse_categorical_accuracy: 0.9507 - scaled_adversarial_loss: 0.0860 - val_loss: 0.1765 - val_sparse_categorical_crossentropy: 0.1130 - val_sparse_categorical_accuracy: 0.9566 - val_scaled_adversarial_loss: 0.0635\n",
      "Epoch 117/1000\n",
      "12/12 [==============================] - 4s 333ms/step - loss: 0.2376 - sparse_categorical_crossentropy: 0.1459 - sparse_categorical_accuracy: 0.9512 - scaled_adversarial_loss: 0.0917 - val_loss: 0.1887 - val_sparse_categorical_crossentropy: 0.1169 - val_sparse_categorical_accuracy: 0.9608 - val_scaled_adversarial_loss: 0.0717\n",
      "Epoch 118/1000\n",
      "12/12 [==============================] - 4s 336ms/step - loss: 0.2390 - sparse_categorical_crossentropy: 0.1485 - sparse_categorical_accuracy: 0.9472 - scaled_adversarial_loss: 0.0905 - val_loss: 0.1707 - val_sparse_categorical_crossentropy: 0.1116 - val_sparse_categorical_accuracy: 0.9608 - val_scaled_adversarial_loss: 0.0591\n",
      "Epoch 119/1000\n",
      "12/12 [==============================] - 4s 332ms/step - loss: 0.2308 - sparse_categorical_crossentropy: 0.1491 - sparse_categorical_accuracy: 0.9484 - scaled_adversarial_loss: 0.0818 - val_loss: 0.1858 - val_sparse_categorical_crossentropy: 0.1235 - val_sparse_categorical_accuracy: 0.9580 - val_scaled_adversarial_loss: 0.0623\n",
      "Epoch 120/1000\n",
      "12/12 [==============================] - 4s 334ms/step - loss: 0.2211 - sparse_categorical_crossentropy: 0.1388 - sparse_categorical_accuracy: 0.9505 - scaled_adversarial_loss: 0.0823 - val_loss: 0.1787 - val_sparse_categorical_crossentropy: 0.1091 - val_sparse_categorical_accuracy: 0.9629 - val_scaled_adversarial_loss: 0.0696\n",
      "Epoch 121/1000\n",
      "12/12 [==============================] - 4s 334ms/step - loss: 0.2295 - sparse_categorical_crossentropy: 0.1434 - sparse_categorical_accuracy: 0.9523 - scaled_adversarial_loss: 0.0861 - val_loss: 0.1823 - val_sparse_categorical_crossentropy: 0.1182 - val_sparse_categorical_accuracy: 0.9685 - val_scaled_adversarial_loss: 0.0640\n",
      "Epoch 122/1000\n",
      "12/12 [==============================] - 4s 336ms/step - loss: 0.2441 - sparse_categorical_crossentropy: 0.1528 - sparse_categorical_accuracy: 0.9509 - scaled_adversarial_loss: 0.0912 - val_loss: 0.1650 - val_sparse_categorical_crossentropy: 0.1104 - val_sparse_categorical_accuracy: 0.9573 - val_scaled_adversarial_loss: 0.0545\n",
      "Epoch 123/1000\n",
      "12/12 [==============================] - 4s 334ms/step - loss: 0.2299 - sparse_categorical_crossentropy: 0.1432 - sparse_categorical_accuracy: 0.9475 - scaled_adversarial_loss: 0.0867 - val_loss: 0.1735 - val_sparse_categorical_crossentropy: 0.1059 - val_sparse_categorical_accuracy: 0.9643 - val_scaled_adversarial_loss: 0.0676\n",
      "Epoch 124/1000\n",
      "12/12 [==============================] - 4s 334ms/step - loss: 0.2321 - sparse_categorical_crossentropy: 0.1363 - sparse_categorical_accuracy: 0.9510 - scaled_adversarial_loss: 0.0958 - val_loss: 0.1873 - val_sparse_categorical_crossentropy: 0.1060 - val_sparse_categorical_accuracy: 0.9643 - val_scaled_adversarial_loss: 0.0814\n",
      "Epoch 125/1000\n",
      "12/12 [==============================] - 4s 347ms/step - loss: 0.2255 - sparse_categorical_crossentropy: 0.1405 - sparse_categorical_accuracy: 0.9537 - scaled_adversarial_loss: 0.0851 - val_loss: 0.2133 - val_sparse_categorical_crossentropy: 0.1317 - val_sparse_categorical_accuracy: 0.9510 - val_scaled_adversarial_loss: 0.0816\n",
      "Epoch 126/1000\n",
      "12/12 [==============================] - 4s 345ms/step - loss: 0.2319 - sparse_categorical_crossentropy: 0.1430 - sparse_categorical_accuracy: 0.9503 - scaled_adversarial_loss: 0.0889 - val_loss: 0.1923 - val_sparse_categorical_crossentropy: 0.1209 - val_sparse_categorical_accuracy: 0.9559 - val_scaled_adversarial_loss: 0.0714\n",
      "Epoch 127/1000\n",
      "12/12 [==============================] - 4s 329ms/step - loss: 0.2404 - sparse_categorical_crossentropy: 0.1463 - sparse_categorical_accuracy: 0.9461 - scaled_adversarial_loss: 0.0941 - val_loss: 0.1735 - val_sparse_categorical_crossentropy: 0.1071 - val_sparse_categorical_accuracy: 0.9706 - val_scaled_adversarial_loss: 0.0664\n",
      "Epoch 128/1000\n",
      "12/12 [==============================] - 4s 363ms/step - loss: 0.2268 - sparse_categorical_crossentropy: 0.1394 - sparse_categorical_accuracy: 0.9531 - scaled_adversarial_loss: 0.0874 - val_loss: 0.1913 - val_sparse_categorical_crossentropy: 0.1192 - val_sparse_categorical_accuracy: 0.9629 - val_scaled_adversarial_loss: 0.0722\n",
      "Epoch 129/1000\n",
      "12/12 [==============================] - 4s 351ms/step - loss: 0.2326 - sparse_categorical_crossentropy: 0.1428 - sparse_categorical_accuracy: 0.9542 - scaled_adversarial_loss: 0.0898 - val_loss: 0.1697 - val_sparse_categorical_crossentropy: 0.1083 - val_sparse_categorical_accuracy: 0.9580 - val_scaled_adversarial_loss: 0.0614\n",
      "Epoch 130/1000\n",
      "12/12 [==============================] - 4s 348ms/step - loss: 0.2071 - sparse_categorical_crossentropy: 0.1243 - sparse_categorical_accuracy: 0.9563 - scaled_adversarial_loss: 0.0828 - val_loss: 0.1867 - val_sparse_categorical_crossentropy: 0.1022 - val_sparse_categorical_accuracy: 0.9636 - val_scaled_adversarial_loss: 0.0845\n",
      "Epoch 131/1000\n",
      "12/12 [==============================] - 4s 348ms/step - loss: 0.2175 - sparse_categorical_crossentropy: 0.1271 - sparse_categorical_accuracy: 0.9528 - scaled_adversarial_loss: 0.0904 - val_loss: 0.1562 - val_sparse_categorical_crossentropy: 0.0957 - val_sparse_categorical_accuracy: 0.9678 - val_scaled_adversarial_loss: 0.0605\n",
      "Epoch 132/1000\n",
      "12/12 [==============================] - 4s 344ms/step - loss: 0.2243 - sparse_categorical_crossentropy: 0.1298 - sparse_categorical_accuracy: 0.9517 - scaled_adversarial_loss: 0.0945 - val_loss: 0.1879 - val_sparse_categorical_crossentropy: 0.0961 - val_sparse_categorical_accuracy: 0.9685 - val_scaled_adversarial_loss: 0.0918\n",
      "Epoch 133/1000\n",
      "12/12 [==============================] - 4s 345ms/step - loss: 0.2214 - sparse_categorical_crossentropy: 0.1268 - sparse_categorical_accuracy: 0.9565 - scaled_adversarial_loss: 0.0946 - val_loss: 0.1608 - val_sparse_categorical_crossentropy: 0.0956 - val_sparse_categorical_accuracy: 0.9685 - val_scaled_adversarial_loss: 0.0651\n",
      "Epoch 134/1000\n",
      "12/12 [==============================] - 4s 337ms/step - loss: 0.2251 - sparse_categorical_crossentropy: 0.1264 - sparse_categorical_accuracy: 0.9531 - scaled_adversarial_loss: 0.0986 - val_loss: 0.1831 - val_sparse_categorical_crossentropy: 0.0931 - val_sparse_categorical_accuracy: 0.9685 - val_scaled_adversarial_loss: 0.0900\n",
      "Epoch 135/1000\n",
      "12/12 [==============================] - 4s 341ms/step - loss: 0.2216 - sparse_categorical_crossentropy: 0.1296 - sparse_categorical_accuracy: 0.9545 - scaled_adversarial_loss: 0.0920 - val_loss: 0.1668 - val_sparse_categorical_crossentropy: 0.1090 - val_sparse_categorical_accuracy: 0.9650 - val_scaled_adversarial_loss: 0.0578\n",
      "Epoch 136/1000\n",
      "12/12 [==============================] - 4s 339ms/step - loss: 0.2200 - sparse_categorical_crossentropy: 0.1256 - sparse_categorical_accuracy: 0.9533 - scaled_adversarial_loss: 0.0945 - val_loss: 0.1724 - val_sparse_categorical_crossentropy: 0.0958 - val_sparse_categorical_accuracy: 0.9692 - val_scaled_adversarial_loss: 0.0766\n",
      "Epoch 137/1000\n",
      "12/12 [==============================] - 4s 338ms/step - loss: 0.2276 - sparse_categorical_crossentropy: 0.1282 - sparse_categorical_accuracy: 0.9524 - scaled_adversarial_loss: 0.0994 - val_loss: 0.1880 - val_sparse_categorical_crossentropy: 0.0939 - val_sparse_categorical_accuracy: 0.9713 - val_scaled_adversarial_loss: 0.0941\n",
      "Epoch 138/1000\n",
      "12/12 [==============================] - 4s 337ms/step - loss: 0.2288 - sparse_categorical_crossentropy: 0.1289 - sparse_categorical_accuracy: 0.9552 - scaled_adversarial_loss: 0.0999 - val_loss: 0.1594 - val_sparse_categorical_crossentropy: 0.0887 - val_sparse_categorical_accuracy: 0.9664 - val_scaled_adversarial_loss: 0.0708\n",
      "Epoch 139/1000\n",
      "12/12 [==============================] - 4s 352ms/step - loss: 0.2257 - sparse_categorical_crossentropy: 0.1257 - sparse_categorical_accuracy: 0.9510 - scaled_adversarial_loss: 0.1000 - val_loss: 0.1910 - val_sparse_categorical_crossentropy: 0.0976 - val_sparse_categorical_accuracy: 0.9699 - val_scaled_adversarial_loss: 0.0934\n",
      "Epoch 140/1000\n",
      "12/12 [==============================] - 4s 359ms/step - loss: 0.2234 - sparse_categorical_crossentropy: 0.1258 - sparse_categorical_accuracy: 0.9540 - scaled_adversarial_loss: 0.0975 - val_loss: 0.1660 - val_sparse_categorical_crossentropy: 0.0868 - val_sparse_categorical_accuracy: 0.9727 - val_scaled_adversarial_loss: 0.0793\n",
      "Epoch 141/1000\n",
      "12/12 [==============================] - 4s 346ms/step - loss: 0.2078 - sparse_categorical_crossentropy: 0.1105 - sparse_categorical_accuracy: 0.9608 - scaled_adversarial_loss: 0.0973 - val_loss: 0.1575 - val_sparse_categorical_crossentropy: 0.0852 - val_sparse_categorical_accuracy: 0.9636 - val_scaled_adversarial_loss: 0.0723\n",
      "Epoch 142/1000\n",
      "12/12 [==============================] - 4s 371ms/step - loss: 0.2225 - sparse_categorical_crossentropy: 0.1240 - sparse_categorical_accuracy: 0.9535 - scaled_adversarial_loss: 0.0984 - val_loss: 0.1630 - val_sparse_categorical_crossentropy: 0.0896 - val_sparse_categorical_accuracy: 0.9678 - val_scaled_adversarial_loss: 0.0734\n",
      "Epoch 143/1000\n",
      "12/12 [==============================] - 4s 363ms/step - loss: 0.2193 - sparse_categorical_crossentropy: 0.1252 - sparse_categorical_accuracy: 0.9556 - scaled_adversarial_loss: 0.0941 - val_loss: 0.1871 - val_sparse_categorical_crossentropy: 0.0996 - val_sparse_categorical_accuracy: 0.9664 - val_scaled_adversarial_loss: 0.0875\n",
      "Epoch 144/1000\n",
      "12/12 [==============================] - 4s 361ms/step - loss: 0.2024 - sparse_categorical_crossentropy: 0.1101 - sparse_categorical_accuracy: 0.9575 - scaled_adversarial_loss: 0.0923 - val_loss: 0.1658 - val_sparse_categorical_crossentropy: 0.0845 - val_sparse_categorical_accuracy: 0.9699 - val_scaled_adversarial_loss: 0.0813\n",
      "Epoch 145/1000\n",
      "12/12 [==============================] - 4s 360ms/step - loss: 0.2041 - sparse_categorical_crossentropy: 0.1132 - sparse_categorical_accuracy: 0.9580 - scaled_adversarial_loss: 0.0909 - val_loss: 0.1410 - val_sparse_categorical_crossentropy: 0.0825 - val_sparse_categorical_accuracy: 0.9699 - val_scaled_adversarial_loss: 0.0585\n",
      "Epoch 146/1000\n",
      "12/12 [==============================] - 4s 365ms/step - loss: 0.2093 - sparse_categorical_crossentropy: 0.1165 - sparse_categorical_accuracy: 0.9587 - scaled_adversarial_loss: 0.0928 - val_loss: 0.1809 - val_sparse_categorical_crossentropy: 0.0832 - val_sparse_categorical_accuracy: 0.9692 - val_scaled_adversarial_loss: 0.0977\n",
      "Epoch 147/1000\n",
      "12/12 [==============================] - 4s 363ms/step - loss: 0.2126 - sparse_categorical_crossentropy: 0.1098 - sparse_categorical_accuracy: 0.9601 - scaled_adversarial_loss: 0.1028 - val_loss: 0.1762 - val_sparse_categorical_crossentropy: 0.0998 - val_sparse_categorical_accuracy: 0.9657 - val_scaled_adversarial_loss: 0.0764\n",
      "Epoch 148/1000\n",
      "12/12 [==============================] - 4s 350ms/step - loss: 0.2202 - sparse_categorical_crossentropy: 0.1182 - sparse_categorical_accuracy: 0.9594 - scaled_adversarial_loss: 0.1021 - val_loss: 0.1570 - val_sparse_categorical_crossentropy: 0.0768 - val_sparse_categorical_accuracy: 0.9692 - val_scaled_adversarial_loss: 0.0802\n",
      "Epoch 149/1000\n",
      "12/12 [==============================] - 4s 347ms/step - loss: 0.2129 - sparse_categorical_crossentropy: 0.1173 - sparse_categorical_accuracy: 0.9559 - scaled_adversarial_loss: 0.0956 - val_loss: 0.1577 - val_sparse_categorical_crossentropy: 0.0901 - val_sparse_categorical_accuracy: 0.9678 - val_scaled_adversarial_loss: 0.0677\n",
      "Epoch 150/1000\n",
      "12/12 [==============================] - 4s 343ms/step - loss: 0.2144 - sparse_categorical_crossentropy: 0.1182 - sparse_categorical_accuracy: 0.9587 - scaled_adversarial_loss: 0.0962 - val_loss: 0.1541 - val_sparse_categorical_crossentropy: 0.0846 - val_sparse_categorical_accuracy: 0.9741 - val_scaled_adversarial_loss: 0.0695\n",
      "Epoch 151/1000\n",
      "12/12 [==============================] - 4s 334ms/step - loss: 0.2058 - sparse_categorical_crossentropy: 0.1131 - sparse_categorical_accuracy: 0.9593 - scaled_adversarial_loss: 0.0928 - val_loss: 0.1745 - val_sparse_categorical_crossentropy: 0.0859 - val_sparse_categorical_accuracy: 0.9699 - val_scaled_adversarial_loss: 0.0887\n",
      "Epoch 152/1000\n",
      "12/12 [==============================] - 4s 333ms/step - loss: 0.2266 - sparse_categorical_crossentropy: 0.1164 - sparse_categorical_accuracy: 0.9612 - scaled_adversarial_loss: 0.1102 - val_loss: 0.1686 - val_sparse_categorical_crossentropy: 0.0793 - val_sparse_categorical_accuracy: 0.9755 - val_scaled_adversarial_loss: 0.0894\n",
      "Epoch 153/1000\n",
      "12/12 [==============================] - 5s 379ms/step - loss: 0.2029 - sparse_categorical_crossentropy: 0.1028 - sparse_categorical_accuracy: 0.9647 - scaled_adversarial_loss: 0.1000 - val_loss: 0.1508 - val_sparse_categorical_crossentropy: 0.0797 - val_sparse_categorical_accuracy: 0.9720 - val_scaled_adversarial_loss: 0.0711\n",
      "Epoch 154/1000\n",
      "12/12 [==============================] - 4s 355ms/step - loss: 0.1930 - sparse_categorical_crossentropy: 0.1002 - sparse_categorical_accuracy: 0.9671 - scaled_adversarial_loss: 0.0928 - val_loss: 0.1363 - val_sparse_categorical_crossentropy: 0.0783 - val_sparse_categorical_accuracy: 0.9762 - val_scaled_adversarial_loss: 0.0580\n",
      "Epoch 155/1000\n",
      "12/12 [==============================] - 4s 339ms/step - loss: 0.2027 - sparse_categorical_crossentropy: 0.1074 - sparse_categorical_accuracy: 0.9617 - scaled_adversarial_loss: 0.0953 - val_loss: 0.1475 - val_sparse_categorical_crossentropy: 0.0749 - val_sparse_categorical_accuracy: 0.9699 - val_scaled_adversarial_loss: 0.0726\n",
      "Epoch 156/1000\n",
      "12/12 [==============================] - 4s 341ms/step - loss: 0.2057 - sparse_categorical_crossentropy: 0.1159 - sparse_categorical_accuracy: 0.9556 - scaled_adversarial_loss: 0.0898 - val_loss: 0.1495 - val_sparse_categorical_crossentropy: 0.0776 - val_sparse_categorical_accuracy: 0.9685 - val_scaled_adversarial_loss: 0.0719\n",
      "Epoch 157/1000\n",
      "12/12 [==============================] - 4s 333ms/step - loss: 0.2069 - sparse_categorical_crossentropy: 0.1151 - sparse_categorical_accuracy: 0.9552 - scaled_adversarial_loss: 0.0918 - val_loss: 0.1728 - val_sparse_categorical_crossentropy: 0.0974 - val_sparse_categorical_accuracy: 0.9678 - val_scaled_adversarial_loss: 0.0755\n",
      "Epoch 158/1000\n",
      "12/12 [==============================] - 4s 334ms/step - loss: 0.2275 - sparse_categorical_crossentropy: 0.1192 - sparse_categorical_accuracy: 0.9570 - scaled_adversarial_loss: 0.1083 - val_loss: 0.1728 - val_sparse_categorical_crossentropy: 0.0963 - val_sparse_categorical_accuracy: 0.9755 - val_scaled_adversarial_loss: 0.0765\n",
      "Epoch 159/1000\n",
      "12/12 [==============================] - 4s 342ms/step - loss: 0.2052 - sparse_categorical_crossentropy: 0.1129 - sparse_categorical_accuracy: 0.9608 - scaled_adversarial_loss: 0.0923 - val_loss: 0.1549 - val_sparse_categorical_crossentropy: 0.0782 - val_sparse_categorical_accuracy: 0.9692 - val_scaled_adversarial_loss: 0.0766\n",
      "Epoch 160/1000\n",
      "12/12 [==============================] - 4s 359ms/step - loss: 0.1986 - sparse_categorical_crossentropy: 0.1026 - sparse_categorical_accuracy: 0.9656 - scaled_adversarial_loss: 0.0960 - val_loss: 0.1481 - val_sparse_categorical_crossentropy: 0.0769 - val_sparse_categorical_accuracy: 0.9706 - val_scaled_adversarial_loss: 0.0712\n",
      "Epoch 161/1000\n",
      "12/12 [==============================] - 4s 354ms/step - loss: 0.2007 - sparse_categorical_crossentropy: 0.1018 - sparse_categorical_accuracy: 0.9650 - scaled_adversarial_loss: 0.0989 - val_loss: 0.1615 - val_sparse_categorical_crossentropy: 0.0822 - val_sparse_categorical_accuracy: 0.9720 - val_scaled_adversarial_loss: 0.0793\n",
      "Epoch 162/1000\n",
      "12/12 [==============================] - 4s 342ms/step - loss: 0.2089 - sparse_categorical_crossentropy: 0.1068 - sparse_categorical_accuracy: 0.9598 - scaled_adversarial_loss: 0.1021 - val_loss: 0.1472 - val_sparse_categorical_crossentropy: 0.0816 - val_sparse_categorical_accuracy: 0.9734 - val_scaled_adversarial_loss: 0.0655\n",
      "Epoch 163/1000\n",
      "12/12 [==============================] - 4s 339ms/step - loss: 0.1876 - sparse_categorical_crossentropy: 0.0957 - sparse_categorical_accuracy: 0.9668 - scaled_adversarial_loss: 0.0918 - val_loss: 0.1247 - val_sparse_categorical_crossentropy: 0.0656 - val_sparse_categorical_accuracy: 0.9797 - val_scaled_adversarial_loss: 0.0591\n",
      "Epoch 164/1000\n",
      "12/12 [==============================] - 4s 347ms/step - loss: 0.1826 - sparse_categorical_crossentropy: 0.0983 - sparse_categorical_accuracy: 0.9684 - scaled_adversarial_loss: 0.0843 - val_loss: 0.1414 - val_sparse_categorical_crossentropy: 0.0698 - val_sparse_categorical_accuracy: 0.9783 - val_scaled_adversarial_loss: 0.0717\n",
      "Epoch 165/1000\n",
      "12/12 [==============================] - 4s 349ms/step - loss: 0.1906 - sparse_categorical_crossentropy: 0.1017 - sparse_categorical_accuracy: 0.9635 - scaled_adversarial_loss: 0.0889 - val_loss: 0.1365 - val_sparse_categorical_crossentropy: 0.0693 - val_sparse_categorical_accuracy: 0.9755 - val_scaled_adversarial_loss: 0.0672\n",
      "Epoch 166/1000\n",
      "12/12 [==============================] - 4s 342ms/step - loss: 0.1866 - sparse_categorical_crossentropy: 0.0941 - sparse_categorical_accuracy: 0.9680 - scaled_adversarial_loss: 0.0925 - val_loss: 0.1328 - val_sparse_categorical_crossentropy: 0.0709 - val_sparse_categorical_accuracy: 0.9741 - val_scaled_adversarial_loss: 0.0619\n",
      "Epoch 167/1000\n",
      "12/12 [==============================] - 4s 337ms/step - loss: 0.1853 - sparse_categorical_crossentropy: 0.0998 - sparse_categorical_accuracy: 0.9659 - scaled_adversarial_loss: 0.0855 - val_loss: 0.1359 - val_sparse_categorical_crossentropy: 0.0718 - val_sparse_categorical_accuracy: 0.9811 - val_scaled_adversarial_loss: 0.0641\n",
      "Epoch 168/1000\n",
      "12/12 [==============================] - 4s 339ms/step - loss: 0.1793 - sparse_categorical_crossentropy: 0.0913 - sparse_categorical_accuracy: 0.9659 - scaled_adversarial_loss: 0.0880 - val_loss: 0.1329 - val_sparse_categorical_crossentropy: 0.0617 - val_sparse_categorical_accuracy: 0.9804 - val_scaled_adversarial_loss: 0.0712\n",
      "Epoch 169/1000\n",
      "12/12 [==============================] - 4s 337ms/step - loss: 0.1932 - sparse_categorical_crossentropy: 0.1011 - sparse_categorical_accuracy: 0.9661 - scaled_adversarial_loss: 0.0921 - val_loss: 0.1388 - val_sparse_categorical_crossentropy: 0.0623 - val_sparse_categorical_accuracy: 0.9713 - val_scaled_adversarial_loss: 0.0765\n",
      "Epoch 170/1000\n",
      "12/12 [==============================] - 4s 338ms/step - loss: 0.1890 - sparse_categorical_crossentropy: 0.0994 - sparse_categorical_accuracy: 0.9649 - scaled_adversarial_loss: 0.0896 - val_loss: 0.1382 - val_sparse_categorical_crossentropy: 0.0771 - val_sparse_categorical_accuracy: 0.9685 - val_scaled_adversarial_loss: 0.0612\n",
      "Epoch 171/1000\n",
      "12/12 [==============================] - 4s 340ms/step - loss: 0.1880 - sparse_categorical_crossentropy: 0.1014 - sparse_categorical_accuracy: 0.9640 - scaled_adversarial_loss: 0.0866 - val_loss: 0.1256 - val_sparse_categorical_crossentropy: 0.0681 - val_sparse_categorical_accuracy: 0.9797 - val_scaled_adversarial_loss: 0.0575\n",
      "Epoch 172/1000\n",
      "12/12 [==============================] - 4s 335ms/step - loss: 0.1881 - sparse_categorical_crossentropy: 0.0963 - sparse_categorical_accuracy: 0.9661 - scaled_adversarial_loss: 0.0917 - val_loss: 0.1329 - val_sparse_categorical_crossentropy: 0.0709 - val_sparse_categorical_accuracy: 0.9832 - val_scaled_adversarial_loss: 0.0620\n",
      "Epoch 173/1000\n",
      "12/12 [==============================] - 4s 353ms/step - loss: 0.1887 - sparse_categorical_crossentropy: 0.1022 - sparse_categorical_accuracy: 0.9629 - scaled_adversarial_loss: 0.0864 - val_loss: 0.1253 - val_sparse_categorical_crossentropy: 0.0601 - val_sparse_categorical_accuracy: 0.9839 - val_scaled_adversarial_loss: 0.0651\n",
      "Epoch 174/1000\n",
      "12/12 [==============================] - 4s 339ms/step - loss: 0.1942 - sparse_categorical_crossentropy: 0.0988 - sparse_categorical_accuracy: 0.9656 - scaled_adversarial_loss: 0.0954 - val_loss: 0.1269 - val_sparse_categorical_crossentropy: 0.0652 - val_sparse_categorical_accuracy: 0.9790 - val_scaled_adversarial_loss: 0.0617\n",
      "Epoch 175/1000\n",
      "12/12 [==============================] - 4s 340ms/step - loss: 0.1892 - sparse_categorical_crossentropy: 0.0958 - sparse_categorical_accuracy: 0.9650 - scaled_adversarial_loss: 0.0935 - val_loss: 0.1430 - val_sparse_categorical_crossentropy: 0.0645 - val_sparse_categorical_accuracy: 0.9825 - val_scaled_adversarial_loss: 0.0785\n",
      "Epoch 176/1000\n",
      "12/12 [==============================] - 4s 349ms/step - loss: 0.1817 - sparse_categorical_crossentropy: 0.0925 - sparse_categorical_accuracy: 0.9656 - scaled_adversarial_loss: 0.0891 - val_loss: 0.1513 - val_sparse_categorical_crossentropy: 0.0691 - val_sparse_categorical_accuracy: 0.9762 - val_scaled_adversarial_loss: 0.0822\n",
      "Epoch 177/1000\n",
      "12/12 [==============================] - 4s 353ms/step - loss: 0.1826 - sparse_categorical_crossentropy: 0.0955 - sparse_categorical_accuracy: 0.9629 - scaled_adversarial_loss: 0.0871 - val_loss: 0.1250 - val_sparse_categorical_crossentropy: 0.0628 - val_sparse_categorical_accuracy: 0.9783 - val_scaled_adversarial_loss: 0.0623\n",
      "Epoch 178/1000\n",
      "12/12 [==============================] - 4s 357ms/step - loss: 0.1718 - sparse_categorical_crossentropy: 0.0883 - sparse_categorical_accuracy: 0.9675 - scaled_adversarial_loss: 0.0836 - val_loss: 0.1294 - val_sparse_categorical_crossentropy: 0.0619 - val_sparse_categorical_accuracy: 0.9790 - val_scaled_adversarial_loss: 0.0675\n",
      "Epoch 179/1000\n",
      "12/12 [==============================] - 4s 351ms/step - loss: 0.1715 - sparse_categorical_crossentropy: 0.0856 - sparse_categorical_accuracy: 0.9675 - scaled_adversarial_loss: 0.0859 - val_loss: 0.1412 - val_sparse_categorical_crossentropy: 0.0669 - val_sparse_categorical_accuracy: 0.9790 - val_scaled_adversarial_loss: 0.0743\n",
      "Epoch 180/1000\n",
      "12/12 [==============================] - 4s 343ms/step - loss: 0.1796 - sparse_categorical_crossentropy: 0.0892 - sparse_categorical_accuracy: 0.9659 - scaled_adversarial_loss: 0.0904 - val_loss: 0.1053 - val_sparse_categorical_crossentropy: 0.0565 - val_sparse_categorical_accuracy: 0.9811 - val_scaled_adversarial_loss: 0.0488\n",
      "Epoch 181/1000\n",
      "12/12 [==============================] - 4s 359ms/step - loss: 0.1630 - sparse_categorical_crossentropy: 0.0802 - sparse_categorical_accuracy: 0.9684 - scaled_adversarial_loss: 0.0827 - val_loss: 0.1095 - val_sparse_categorical_crossentropy: 0.0588 - val_sparse_categorical_accuracy: 0.9804 - val_scaled_adversarial_loss: 0.0508\n",
      "Epoch 182/1000\n",
      "12/12 [==============================] - 4s 358ms/step - loss: 0.1717 - sparse_categorical_crossentropy: 0.0852 - sparse_categorical_accuracy: 0.9684 - scaled_adversarial_loss: 0.0865 - val_loss: 0.1254 - val_sparse_categorical_crossentropy: 0.0585 - val_sparse_categorical_accuracy: 0.9769 - val_scaled_adversarial_loss: 0.0669\n",
      "Epoch 183/1000\n",
      "12/12 [==============================] - 4s 345ms/step - loss: 0.1708 - sparse_categorical_crossentropy: 0.0908 - sparse_categorical_accuracy: 0.9654 - scaled_adversarial_loss: 0.0801 - val_loss: 0.1194 - val_sparse_categorical_crossentropy: 0.0559 - val_sparse_categorical_accuracy: 0.9804 - val_scaled_adversarial_loss: 0.0635\n",
      "Epoch 184/1000\n",
      "12/12 [==============================] - 4s 335ms/step - loss: 0.1739 - sparse_categorical_crossentropy: 0.0875 - sparse_categorical_accuracy: 0.9666 - scaled_adversarial_loss: 0.0864 - val_loss: 0.1289 - val_sparse_categorical_crossentropy: 0.0629 - val_sparse_categorical_accuracy: 0.9720 - val_scaled_adversarial_loss: 0.0660\n",
      "Epoch 185/1000\n",
      "12/12 [==============================] - 4s 343ms/step - loss: 0.1788 - sparse_categorical_crossentropy: 0.0925 - sparse_categorical_accuracy: 0.9666 - scaled_adversarial_loss: 0.0863 - val_loss: 0.1214 - val_sparse_categorical_crossentropy: 0.0568 - val_sparse_categorical_accuracy: 0.9804 - val_scaled_adversarial_loss: 0.0646\n",
      "Epoch 186/1000\n",
      "12/12 [==============================] - 4s 338ms/step - loss: 0.1705 - sparse_categorical_crossentropy: 0.0848 - sparse_categorical_accuracy: 0.9697 - scaled_adversarial_loss: 0.0858 - val_loss: 0.1153 - val_sparse_categorical_crossentropy: 0.0601 - val_sparse_categorical_accuracy: 0.9783 - val_scaled_adversarial_loss: 0.0552\n",
      "Epoch 187/1000\n",
      "12/12 [==============================] - 4s 332ms/step - loss: 0.1820 - sparse_categorical_crossentropy: 0.0903 - sparse_categorical_accuracy: 0.9673 - scaled_adversarial_loss: 0.0917 - val_loss: 0.1442 - val_sparse_categorical_crossentropy: 0.0745 - val_sparse_categorical_accuracy: 0.9727 - val_scaled_adversarial_loss: 0.0697\n",
      "Epoch 188/1000\n",
      "12/12 [==============================] - 4s 334ms/step - loss: 0.1735 - sparse_categorical_crossentropy: 0.0890 - sparse_categorical_accuracy: 0.9661 - scaled_adversarial_loss: 0.0845 - val_loss: 0.1316 - val_sparse_categorical_crossentropy: 0.0628 - val_sparse_categorical_accuracy: 0.9783 - val_scaled_adversarial_loss: 0.0688\n",
      "Epoch 189/1000\n",
      "12/12 [==============================] - 4s 336ms/step - loss: 0.1774 - sparse_categorical_crossentropy: 0.0873 - sparse_categorical_accuracy: 0.9684 - scaled_adversarial_loss: 0.0900 - val_loss: 0.1218 - val_sparse_categorical_crossentropy: 0.0648 - val_sparse_categorical_accuracy: 0.9720 - val_scaled_adversarial_loss: 0.0570\n",
      "Epoch 190/1000\n",
      "12/12 [==============================] - 4s 334ms/step - loss: 0.1832 - sparse_categorical_crossentropy: 0.0935 - sparse_categorical_accuracy: 0.9647 - scaled_adversarial_loss: 0.0897 - val_loss: 0.1596 - val_sparse_categorical_crossentropy: 0.0765 - val_sparse_categorical_accuracy: 0.9720 - val_scaled_adversarial_loss: 0.0831\n",
      "Epoch 191/1000\n",
      "12/12 [==============================] - 4s 334ms/step - loss: 0.1896 - sparse_categorical_crossentropy: 0.0928 - sparse_categorical_accuracy: 0.9673 - scaled_adversarial_loss: 0.0968 - val_loss: 0.1203 - val_sparse_categorical_crossentropy: 0.0634 - val_sparse_categorical_accuracy: 0.9769 - val_scaled_adversarial_loss: 0.0569\n",
      "Epoch 192/1000\n",
      "12/12 [==============================] - 4s 342ms/step - loss: 0.1842 - sparse_categorical_crossentropy: 0.0939 - sparse_categorical_accuracy: 0.9671 - scaled_adversarial_loss: 0.0903 - val_loss: 0.1404 - val_sparse_categorical_crossentropy: 0.0727 - val_sparse_categorical_accuracy: 0.9776 - val_scaled_adversarial_loss: 0.0676\n",
      "Epoch 193/1000\n",
      "12/12 [==============================] - 4s 345ms/step - loss: 0.1831 - sparse_categorical_crossentropy: 0.0942 - sparse_categorical_accuracy: 0.9677 - scaled_adversarial_loss: 0.0888 - val_loss: 0.1337 - val_sparse_categorical_crossentropy: 0.0634 - val_sparse_categorical_accuracy: 0.9832 - val_scaled_adversarial_loss: 0.0702\n",
      "Epoch 194/1000\n",
      "12/12 [==============================] - 4s 351ms/step - loss: 0.1739 - sparse_categorical_crossentropy: 0.0904 - sparse_categorical_accuracy: 0.9670 - scaled_adversarial_loss: 0.0835 - val_loss: 0.1392 - val_sparse_categorical_crossentropy: 0.0626 - val_sparse_categorical_accuracy: 0.9776 - val_scaled_adversarial_loss: 0.0765\n",
      "Epoch 195/1000\n",
      "12/12 [==============================] - 4s 342ms/step - loss: 0.1801 - sparse_categorical_crossentropy: 0.0940 - sparse_categorical_accuracy: 0.9678 - scaled_adversarial_loss: 0.0861 - val_loss: 0.1327 - val_sparse_categorical_crossentropy: 0.0643 - val_sparse_categorical_accuracy: 0.9797 - val_scaled_adversarial_loss: 0.0684\n",
      "Epoch 196/1000\n",
      "12/12 [==============================] - 4s 341ms/step - loss: 0.1768 - sparse_categorical_crossentropy: 0.0941 - sparse_categorical_accuracy: 0.9663 - scaled_adversarial_loss: 0.0827 - val_loss: 0.1444 - val_sparse_categorical_crossentropy: 0.0655 - val_sparse_categorical_accuracy: 0.9832 - val_scaled_adversarial_loss: 0.0789\n",
      "Epoch 197/1000\n",
      "12/12 [==============================] - 4s 338ms/step - loss: 0.1660 - sparse_categorical_crossentropy: 0.0824 - sparse_categorical_accuracy: 0.9718 - scaled_adversarial_loss: 0.0836 - val_loss: 0.1248 - val_sparse_categorical_crossentropy: 0.0621 - val_sparse_categorical_accuracy: 0.9797 - val_scaled_adversarial_loss: 0.0627\n",
      "Epoch 198/1000\n",
      "12/12 [==============================] - 4s 335ms/step - loss: 0.1714 - sparse_categorical_crossentropy: 0.0828 - sparse_categorical_accuracy: 0.9677 - scaled_adversarial_loss: 0.0886 - val_loss: 0.1199 - val_sparse_categorical_crossentropy: 0.0585 - val_sparse_categorical_accuracy: 0.9818 - val_scaled_adversarial_loss: 0.0615\n",
      "Epoch 199/1000\n",
      "12/12 [==============================] - 4s 348ms/step - loss: 0.1717 - sparse_categorical_crossentropy: 0.0791 - sparse_categorical_accuracy: 0.9713 - scaled_adversarial_loss: 0.0926 - val_loss: 0.1422 - val_sparse_categorical_crossentropy: 0.0612 - val_sparse_categorical_accuracy: 0.9783 - val_scaled_adversarial_loss: 0.0810\n",
      "Epoch 200/1000\n",
      "12/12 [==============================] - 4s 336ms/step - loss: 0.1728 - sparse_categorical_crossentropy: 0.0785 - sparse_categorical_accuracy: 0.9706 - scaled_adversarial_loss: 0.0944 - val_loss: 0.1315 - val_sparse_categorical_crossentropy: 0.0497 - val_sparse_categorical_accuracy: 0.9860 - val_scaled_adversarial_loss: 0.0818\n",
      "Epoch 201/1000\n",
      "12/12 [==============================] - 4s 346ms/step - loss: 0.1694 - sparse_categorical_crossentropy: 0.0762 - sparse_categorical_accuracy: 0.9722 - scaled_adversarial_loss: 0.0932 - val_loss: 0.1236 - val_sparse_categorical_crossentropy: 0.0519 - val_sparse_categorical_accuracy: 0.9825 - val_scaled_adversarial_loss: 0.0718\n",
      "Epoch 202/1000\n",
      "12/12 [==============================] - 4s 357ms/step - loss: 0.1710 - sparse_categorical_crossentropy: 0.0758 - sparse_categorical_accuracy: 0.9753 - scaled_adversarial_loss: 0.0951 - val_loss: 0.1294 - val_sparse_categorical_crossentropy: 0.0511 - val_sparse_categorical_accuracy: 0.9853 - val_scaled_adversarial_loss: 0.0783\n",
      "Epoch 203/1000\n",
      "12/12 [==============================] - 4s 340ms/step - loss: 0.1646 - sparse_categorical_crossentropy: 0.0784 - sparse_categorical_accuracy: 0.9732 - scaled_adversarial_loss: 0.0861 - val_loss: 0.1068 - val_sparse_categorical_crossentropy: 0.0469 - val_sparse_categorical_accuracy: 0.9860 - val_scaled_adversarial_loss: 0.0599\n",
      "Epoch 204/1000\n",
      "12/12 [==============================] - 4s 348ms/step - loss: 0.1647 - sparse_categorical_crossentropy: 0.0760 - sparse_categorical_accuracy: 0.9720 - scaled_adversarial_loss: 0.0887 - val_loss: 0.1135 - val_sparse_categorical_crossentropy: 0.0544 - val_sparse_categorical_accuracy: 0.9825 - val_scaled_adversarial_loss: 0.0591\n",
      "Epoch 205/1000\n",
      "12/12 [==============================] - 4s 356ms/step - loss: 0.1565 - sparse_categorical_crossentropy: 0.0749 - sparse_categorical_accuracy: 0.9734 - scaled_adversarial_loss: 0.0816 - val_loss: 0.1192 - val_sparse_categorical_crossentropy: 0.0497 - val_sparse_categorical_accuracy: 0.9811 - val_scaled_adversarial_loss: 0.0695\n",
      "Epoch 206/1000\n",
      "12/12 [==============================] - 4s 365ms/step - loss: 0.1604 - sparse_categorical_crossentropy: 0.0733 - sparse_categorical_accuracy: 0.9746 - scaled_adversarial_loss: 0.0872 - val_loss: 0.1180 - val_sparse_categorical_crossentropy: 0.0567 - val_sparse_categorical_accuracy: 0.9797 - val_scaled_adversarial_loss: 0.0613\n",
      "Epoch 207/1000\n",
      "12/12 [==============================] - 4s 347ms/step - loss: 0.1666 - sparse_categorical_crossentropy: 0.0814 - sparse_categorical_accuracy: 0.9689 - scaled_adversarial_loss: 0.0852 - val_loss: 0.1131 - val_sparse_categorical_crossentropy: 0.0560 - val_sparse_categorical_accuracy: 0.9867 - val_scaled_adversarial_loss: 0.0571\n",
      "Epoch 208/1000\n",
      "12/12 [==============================] - 4s 345ms/step - loss: 0.1571 - sparse_categorical_crossentropy: 0.0785 - sparse_categorical_accuracy: 0.9732 - scaled_adversarial_loss: 0.0786 - val_loss: 0.1154 - val_sparse_categorical_crossentropy: 0.0490 - val_sparse_categorical_accuracy: 0.9846 - val_scaled_adversarial_loss: 0.0664\n",
      "Epoch 209/1000\n",
      "12/12 [==============================] - 4s 351ms/step - loss: 0.1563 - sparse_categorical_crossentropy: 0.0740 - sparse_categorical_accuracy: 0.9741 - scaled_adversarial_loss: 0.0824 - val_loss: 0.1108 - val_sparse_categorical_crossentropy: 0.0448 - val_sparse_categorical_accuracy: 0.9846 - val_scaled_adversarial_loss: 0.0659\n",
      "Epoch 210/1000\n",
      "12/12 [==============================] - 4s 368ms/step - loss: 0.1628 - sparse_categorical_crossentropy: 0.0778 - sparse_categorical_accuracy: 0.9755 - scaled_adversarial_loss: 0.0850 - val_loss: 0.1193 - val_sparse_categorical_crossentropy: 0.0511 - val_sparse_categorical_accuracy: 0.9839 - val_scaled_adversarial_loss: 0.0682\n",
      "Epoch 211/1000\n",
      "12/12 [==============================] - 4s 363ms/step - loss: 0.1615 - sparse_categorical_crossentropy: 0.0778 - sparse_categorical_accuracy: 0.9741 - scaled_adversarial_loss: 0.0837 - val_loss: 0.1234 - val_sparse_categorical_crossentropy: 0.0540 - val_sparse_categorical_accuracy: 0.9818 - val_scaled_adversarial_loss: 0.0694\n",
      "Epoch 212/1000\n",
      "12/12 [==============================] - 4s 369ms/step - loss: 0.1636 - sparse_categorical_crossentropy: 0.0812 - sparse_categorical_accuracy: 0.9696 - scaled_adversarial_loss: 0.0824 - val_loss: 0.1205 - val_sparse_categorical_crossentropy: 0.0516 - val_sparse_categorical_accuracy: 0.9825 - val_scaled_adversarial_loss: 0.0689\n",
      "Epoch 213/1000\n",
      "12/12 [==============================] - 4s 358ms/step - loss: 0.1549 - sparse_categorical_crossentropy: 0.0738 - sparse_categorical_accuracy: 0.9736 - scaled_adversarial_loss: 0.0811 - val_loss: 0.1069 - val_sparse_categorical_crossentropy: 0.0501 - val_sparse_categorical_accuracy: 0.9839 - val_scaled_adversarial_loss: 0.0568\n",
      "Epoch 214/1000\n",
      "12/12 [==============================] - 4s 353ms/step - loss: 0.1669 - sparse_categorical_crossentropy: 0.0792 - sparse_categorical_accuracy: 0.9725 - scaled_adversarial_loss: 0.0876 - val_loss: 0.1253 - val_sparse_categorical_crossentropy: 0.0547 - val_sparse_categorical_accuracy: 0.9811 - val_scaled_adversarial_loss: 0.0705\n",
      "Epoch 215/1000\n",
      "12/12 [==============================] - 4s 346ms/step - loss: 0.1625 - sparse_categorical_crossentropy: 0.0777 - sparse_categorical_accuracy: 0.9734 - scaled_adversarial_loss: 0.0848 - val_loss: 0.1239 - val_sparse_categorical_crossentropy: 0.0589 - val_sparse_categorical_accuracy: 0.9811 - val_scaled_adversarial_loss: 0.0650\n",
      "Epoch 216/1000\n",
      "12/12 [==============================] - 4s 346ms/step - loss: 0.1637 - sparse_categorical_crossentropy: 0.0771 - sparse_categorical_accuracy: 0.9727 - scaled_adversarial_loss: 0.0867 - val_loss: 0.1092 - val_sparse_categorical_crossentropy: 0.0476 - val_sparse_categorical_accuracy: 0.9846 - val_scaled_adversarial_loss: 0.0616\n",
      "Epoch 217/1000\n",
      "12/12 [==============================] - 4s 341ms/step - loss: 0.1607 - sparse_categorical_crossentropy: 0.0783 - sparse_categorical_accuracy: 0.9727 - scaled_adversarial_loss: 0.0824 - val_loss: 0.1144 - val_sparse_categorical_crossentropy: 0.0512 - val_sparse_categorical_accuracy: 0.9846 - val_scaled_adversarial_loss: 0.0632\n",
      "Epoch 218/1000\n",
      "12/12 [==============================] - 4s 346ms/step - loss: 0.1626 - sparse_categorical_crossentropy: 0.0759 - sparse_categorical_accuracy: 0.9741 - scaled_adversarial_loss: 0.0867 - val_loss: 0.1204 - val_sparse_categorical_crossentropy: 0.0563 - val_sparse_categorical_accuracy: 0.9797 - val_scaled_adversarial_loss: 0.0642\n",
      "Epoch 219/1000\n",
      "12/12 [==============================] - 4s 347ms/step - loss: 0.1583 - sparse_categorical_crossentropy: 0.0760 - sparse_categorical_accuracy: 0.9741 - scaled_adversarial_loss: 0.0824 - val_loss: 0.1034 - val_sparse_categorical_crossentropy: 0.0514 - val_sparse_categorical_accuracy: 0.9832 - val_scaled_adversarial_loss: 0.0520\n",
      "Epoch 220/1000\n",
      "12/12 [==============================] - 4s 344ms/step - loss: 0.1741 - sparse_categorical_crossentropy: 0.0911 - sparse_categorical_accuracy: 0.9722 - scaled_adversarial_loss: 0.0830 - val_loss: 0.1255 - val_sparse_categorical_crossentropy: 0.0600 - val_sparse_categorical_accuracy: 0.9818 - val_scaled_adversarial_loss: 0.0656\n",
      "Epoch 221/1000\n",
      "12/12 [==============================] - 4s 349ms/step - loss: 0.1697 - sparse_categorical_crossentropy: 0.0871 - sparse_categorical_accuracy: 0.9687 - scaled_adversarial_loss: 0.0827 - val_loss: 0.1135 - val_sparse_categorical_crossentropy: 0.0541 - val_sparse_categorical_accuracy: 0.9783 - val_scaled_adversarial_loss: 0.0593\n",
      "Epoch 222/1000\n",
      "12/12 [==============================] - 4s 351ms/step - loss: 0.1478 - sparse_categorical_crossentropy: 0.0713 - sparse_categorical_accuracy: 0.9759 - scaled_adversarial_loss: 0.0765 - val_loss: 0.0966 - val_sparse_categorical_crossentropy: 0.0448 - val_sparse_categorical_accuracy: 0.9846 - val_scaled_adversarial_loss: 0.0518\n",
      "Epoch 223/1000\n",
      "12/12 [==============================] - 4s 335ms/step - loss: 0.1579 - sparse_categorical_crossentropy: 0.0751 - sparse_categorical_accuracy: 0.9766 - scaled_adversarial_loss: 0.0828 - val_loss: 0.1154 - val_sparse_categorical_crossentropy: 0.0501 - val_sparse_categorical_accuracy: 0.9839 - val_scaled_adversarial_loss: 0.0654\n",
      "Epoch 224/1000\n",
      "12/12 [==============================] - 4s 338ms/step - loss: 0.1562 - sparse_categorical_crossentropy: 0.0748 - sparse_categorical_accuracy: 0.9755 - scaled_adversarial_loss: 0.0814 - val_loss: 0.0934 - val_sparse_categorical_crossentropy: 0.0513 - val_sparse_categorical_accuracy: 0.9811 - val_scaled_adversarial_loss: 0.0421\n",
      "Epoch 225/1000\n",
      "12/12 [==============================] - 4s 338ms/step - loss: 0.1506 - sparse_categorical_crossentropy: 0.0693 - sparse_categorical_accuracy: 0.9732 - scaled_adversarial_loss: 0.0813 - val_loss: 0.1039 - val_sparse_categorical_crossentropy: 0.0493 - val_sparse_categorical_accuracy: 0.9846 - val_scaled_adversarial_loss: 0.0546\n",
      "Epoch 226/1000\n",
      "12/12 [==============================] - 4s 335ms/step - loss: 0.1571 - sparse_categorical_crossentropy: 0.0724 - sparse_categorical_accuracy: 0.9741 - scaled_adversarial_loss: 0.0848 - val_loss: 0.1134 - val_sparse_categorical_crossentropy: 0.0528 - val_sparse_categorical_accuracy: 0.9804 - val_scaled_adversarial_loss: 0.0605\n",
      "Epoch 227/1000\n",
      "12/12 [==============================] - 4s 340ms/step - loss: 0.1767 - sparse_categorical_crossentropy: 0.0883 - sparse_categorical_accuracy: 0.9685 - scaled_adversarial_loss: 0.0884 - val_loss: 0.1215 - val_sparse_categorical_crossentropy: 0.0545 - val_sparse_categorical_accuracy: 0.9804 - val_scaled_adversarial_loss: 0.0669\n",
      "Epoch 228/1000\n",
      "12/12 [==============================] - 4s 335ms/step - loss: 0.1698 - sparse_categorical_crossentropy: 0.0729 - sparse_categorical_accuracy: 0.9764 - scaled_adversarial_loss: 0.0969 - val_loss: 0.1256 - val_sparse_categorical_crossentropy: 0.0563 - val_sparse_categorical_accuracy: 0.9846 - val_scaled_adversarial_loss: 0.0694\n",
      "Epoch 229/1000\n",
      "12/12 [==============================] - 4s 361ms/step - loss: 0.1654 - sparse_categorical_crossentropy: 0.0767 - sparse_categorical_accuracy: 0.9731 - scaled_adversarial_loss: 0.0887 - val_loss: 0.1022 - val_sparse_categorical_crossentropy: 0.0467 - val_sparse_categorical_accuracy: 0.9846 - val_scaled_adversarial_loss: 0.0555\n",
      "Epoch 230/1000\n",
      "12/12 [==============================] - 4s 352ms/step - loss: 0.1425 - sparse_categorical_crossentropy: 0.0675 - sparse_categorical_accuracy: 0.9748 - scaled_adversarial_loss: 0.0751 - val_loss: 0.1004 - val_sparse_categorical_crossentropy: 0.0510 - val_sparse_categorical_accuracy: 0.9818 - val_scaled_adversarial_loss: 0.0494\n",
      "Epoch 231/1000\n",
      "12/12 [==============================] - 4s 351ms/step - loss: 0.1474 - sparse_categorical_crossentropy: 0.0672 - sparse_categorical_accuracy: 0.9755 - scaled_adversarial_loss: 0.0802 - val_loss: 0.0955 - val_sparse_categorical_crossentropy: 0.0461 - val_sparse_categorical_accuracy: 0.9832 - val_scaled_adversarial_loss: 0.0494\n",
      "Epoch 232/1000\n",
      "12/12 [==============================] - 4s 351ms/step - loss: 0.1662 - sparse_categorical_crossentropy: 0.0770 - sparse_categorical_accuracy: 0.9748 - scaled_adversarial_loss: 0.0892 - val_loss: 0.1047 - val_sparse_categorical_crossentropy: 0.0500 - val_sparse_categorical_accuracy: 0.9832 - val_scaled_adversarial_loss: 0.0547\n",
      "Epoch 233/1000\n",
      "12/12 [==============================] - 4s 346ms/step - loss: 0.1530 - sparse_categorical_crossentropy: 0.0683 - sparse_categorical_accuracy: 0.9774 - scaled_adversarial_loss: 0.0848 - val_loss: 0.0964 - val_sparse_categorical_crossentropy: 0.0478 - val_sparse_categorical_accuracy: 0.9832 - val_scaled_adversarial_loss: 0.0486\n",
      "Epoch 234/1000\n",
      "12/12 [==============================] - 4s 340ms/step - loss: 0.1503 - sparse_categorical_crossentropy: 0.0700 - sparse_categorical_accuracy: 0.9766 - scaled_adversarial_loss: 0.0804 - val_loss: 0.0962 - val_sparse_categorical_crossentropy: 0.0438 - val_sparse_categorical_accuracy: 0.9846 - val_scaled_adversarial_loss: 0.0524\n",
      "Epoch 235/1000\n",
      "12/12 [==============================] - 4s 338ms/step - loss: 0.1440 - sparse_categorical_crossentropy: 0.0628 - sparse_categorical_accuracy: 0.9767 - scaled_adversarial_loss: 0.0811 - val_loss: 0.1063 - val_sparse_categorical_crossentropy: 0.0511 - val_sparse_categorical_accuracy: 0.9846 - val_scaled_adversarial_loss: 0.0552\n",
      "Epoch 236/1000\n",
      "12/12 [==============================] - 4s 347ms/step - loss: 0.1518 - sparse_categorical_crossentropy: 0.0663 - sparse_categorical_accuracy: 0.9774 - scaled_adversarial_loss: 0.0855 - val_loss: 0.0976 - val_sparse_categorical_crossentropy: 0.0472 - val_sparse_categorical_accuracy: 0.9853 - val_scaled_adversarial_loss: 0.0504\n",
      "Epoch 237/1000\n",
      "12/12 [==============================] - 4s 350ms/step - loss: 0.1542 - sparse_categorical_crossentropy: 0.0688 - sparse_categorical_accuracy: 0.9764 - scaled_adversarial_loss: 0.0855 - val_loss: 0.1101 - val_sparse_categorical_crossentropy: 0.0466 - val_sparse_categorical_accuracy: 0.9853 - val_scaled_adversarial_loss: 0.0635\n",
      "Epoch 238/1000\n",
      "12/12 [==============================] - 4s 350ms/step - loss: 0.1770 - sparse_categorical_crossentropy: 0.0884 - sparse_categorical_accuracy: 0.9692 - scaled_adversarial_loss: 0.0886 - val_loss: 0.0943 - val_sparse_categorical_crossentropy: 0.0520 - val_sparse_categorical_accuracy: 0.9860 - val_scaled_adversarial_loss: 0.0423\n",
      "Epoch 239/1000\n",
      "12/12 [==============================] - 4s 347ms/step - loss: 0.1661 - sparse_categorical_crossentropy: 0.0817 - sparse_categorical_accuracy: 0.9704 - scaled_adversarial_loss: 0.0844 - val_loss: 0.1057 - val_sparse_categorical_crossentropy: 0.0475 - val_sparse_categorical_accuracy: 0.9818 - val_scaled_adversarial_loss: 0.0582\n",
      "Epoch 240/1000\n",
      "12/12 [==============================] - 4s 342ms/step - loss: 0.1630 - sparse_categorical_crossentropy: 0.0781 - sparse_categorical_accuracy: 0.9699 - scaled_adversarial_loss: 0.0849 - val_loss: 0.1102 - val_sparse_categorical_crossentropy: 0.0469 - val_sparse_categorical_accuracy: 0.9881 - val_scaled_adversarial_loss: 0.0633\n",
      "Epoch 241/1000\n",
      "12/12 [==============================] - 4s 341ms/step - loss: 0.1547 - sparse_categorical_crossentropy: 0.0687 - sparse_categorical_accuracy: 0.9750 - scaled_adversarial_loss: 0.0860 - val_loss: 0.1038 - val_sparse_categorical_crossentropy: 0.0473 - val_sparse_categorical_accuracy: 0.9846 - val_scaled_adversarial_loss: 0.0565\n",
      "Epoch 242/1000\n",
      "12/12 [==============================] - 4s 352ms/step - loss: 0.1412 - sparse_categorical_crossentropy: 0.0605 - sparse_categorical_accuracy: 0.9795 - scaled_adversarial_loss: 0.0806 - val_loss: 0.1014 - val_sparse_categorical_crossentropy: 0.0478 - val_sparse_categorical_accuracy: 0.9832 - val_scaled_adversarial_loss: 0.0536\n",
      "Epoch 243/1000\n",
      "12/12 [==============================] - 4s 345ms/step - loss: 0.1436 - sparse_categorical_crossentropy: 0.0623 - sparse_categorical_accuracy: 0.9771 - scaled_adversarial_loss: 0.0813 - val_loss: 0.0972 - val_sparse_categorical_crossentropy: 0.0472 - val_sparse_categorical_accuracy: 0.9867 - val_scaled_adversarial_loss: 0.0500\n",
      "Epoch 244/1000\n",
      "12/12 [==============================] - 4s 336ms/step - loss: 0.1395 - sparse_categorical_crossentropy: 0.0606 - sparse_categorical_accuracy: 0.9795 - scaled_adversarial_loss: 0.0788 - val_loss: 0.1000 - val_sparse_categorical_crossentropy: 0.0420 - val_sparse_categorical_accuracy: 0.9846 - val_scaled_adversarial_loss: 0.0581\n",
      "Epoch 245/1000\n",
      "12/12 [==============================] - 4s 368ms/step - loss: 0.1625 - sparse_categorical_crossentropy: 0.0757 - sparse_categorical_accuracy: 0.9739 - scaled_adversarial_loss: 0.0867 - val_loss: 0.1182 - val_sparse_categorical_crossentropy: 0.0545 - val_sparse_categorical_accuracy: 0.9839 - val_scaled_adversarial_loss: 0.0637\n",
      "Epoch 246/1000\n",
      "12/12 [==============================] - 4s 349ms/step - loss: 0.1637 - sparse_categorical_crossentropy: 0.0771 - sparse_categorical_accuracy: 0.9762 - scaled_adversarial_loss: 0.0866 - val_loss: 0.1010 - val_sparse_categorical_crossentropy: 0.0555 - val_sparse_categorical_accuracy: 0.9755 - val_scaled_adversarial_loss: 0.0455\n",
      "Epoch 247/1000\n",
      "12/12 [==============================] - 4s 350ms/step - loss: 0.1783 - sparse_categorical_crossentropy: 0.0958 - sparse_categorical_accuracy: 0.9628 - scaled_adversarial_loss: 0.0825 - val_loss: 0.1310 - val_sparse_categorical_crossentropy: 0.0745 - val_sparse_categorical_accuracy: 0.9678 - val_scaled_adversarial_loss: 0.0565\n",
      "Epoch 248/1000\n",
      "12/12 [==============================] - 4s 351ms/step - loss: 0.1668 - sparse_categorical_crossentropy: 0.0812 - sparse_categorical_accuracy: 0.9736 - scaled_adversarial_loss: 0.0856 - val_loss: 0.1147 - val_sparse_categorical_crossentropy: 0.0502 - val_sparse_categorical_accuracy: 0.9867 - val_scaled_adversarial_loss: 0.0645\n",
      "Epoch 249/1000\n",
      "12/12 [==============================] - 4s 334ms/step - loss: 0.1588 - sparse_categorical_crossentropy: 0.0749 - sparse_categorical_accuracy: 0.9732 - scaled_adversarial_loss: 0.0839 - val_loss: 0.1029 - val_sparse_categorical_crossentropy: 0.0516 - val_sparse_categorical_accuracy: 0.9804 - val_scaled_adversarial_loss: 0.0514\n",
      "Epoch 250/1000\n",
      "12/12 [==============================] - 4s 333ms/step - loss: 0.1600 - sparse_categorical_crossentropy: 0.0746 - sparse_categorical_accuracy: 0.9752 - scaled_adversarial_loss: 0.0855 - val_loss: 0.1024 - val_sparse_categorical_crossentropy: 0.0480 - val_sparse_categorical_accuracy: 0.9832 - val_scaled_adversarial_loss: 0.0544\n",
      "Epoch 251/1000\n",
      "12/12 [==============================] - 4s 338ms/step - loss: 0.1424 - sparse_categorical_crossentropy: 0.0599 - sparse_categorical_accuracy: 0.9792 - scaled_adversarial_loss: 0.0824 - val_loss: 0.0903 - val_sparse_categorical_crossentropy: 0.0417 - val_sparse_categorical_accuracy: 0.9860 - val_scaled_adversarial_loss: 0.0486\n",
      "Epoch 252/1000\n",
      "12/12 [==============================] - 4s 337ms/step - loss: 0.1515 - sparse_categorical_crossentropy: 0.0686 - sparse_categorical_accuracy: 0.9752 - scaled_adversarial_loss: 0.0828 - val_loss: 0.1025 - val_sparse_categorical_crossentropy: 0.0455 - val_sparse_categorical_accuracy: 0.9867 - val_scaled_adversarial_loss: 0.0571\n",
      "Epoch 253/1000\n",
      "12/12 [==============================] - 4s 337ms/step - loss: 0.1527 - sparse_categorical_crossentropy: 0.0695 - sparse_categorical_accuracy: 0.9773 - scaled_adversarial_loss: 0.0833 - val_loss: 0.0982 - val_sparse_categorical_crossentropy: 0.0513 - val_sparse_categorical_accuracy: 0.9846 - val_scaled_adversarial_loss: 0.0470\n",
      "Epoch 254/1000\n",
      "12/12 [==============================] - 4s 341ms/step - loss: 0.1471 - sparse_categorical_crossentropy: 0.0693 - sparse_categorical_accuracy: 0.9762 - scaled_adversarial_loss: 0.0778 - val_loss: 0.0977 - val_sparse_categorical_crossentropy: 0.0464 - val_sparse_categorical_accuracy: 0.9860 - val_scaled_adversarial_loss: 0.0513\n",
      "Epoch 255/1000\n",
      "12/12 [==============================] - 4s 339ms/step - loss: 0.1450 - sparse_categorical_crossentropy: 0.0622 - sparse_categorical_accuracy: 0.9780 - scaled_adversarial_loss: 0.0827 - val_loss: 0.0959 - val_sparse_categorical_crossentropy: 0.0422 - val_sparse_categorical_accuracy: 0.9867 - val_scaled_adversarial_loss: 0.0537\n",
      "Epoch 256/1000\n",
      "12/12 [==============================] - 4s 336ms/step - loss: 0.1530 - sparse_categorical_crossentropy: 0.0662 - sparse_categorical_accuracy: 0.9792 - scaled_adversarial_loss: 0.0868 - val_loss: 0.1079 - val_sparse_categorical_crossentropy: 0.0475 - val_sparse_categorical_accuracy: 0.9860 - val_scaled_adversarial_loss: 0.0604\n",
      "Epoch 257/1000\n",
      "12/12 [==============================] - 4s 334ms/step - loss: 0.1539 - sparse_categorical_crossentropy: 0.0673 - sparse_categorical_accuracy: 0.9746 - scaled_adversarial_loss: 0.0866 - val_loss: 0.1143 - val_sparse_categorical_crossentropy: 0.0605 - val_sparse_categorical_accuracy: 0.9832 - val_scaled_adversarial_loss: 0.0537\n",
      "Epoch 258/1000\n",
      "12/12 [==============================] - 4s 338ms/step - loss: 0.1554 - sparse_categorical_crossentropy: 0.0737 - sparse_categorical_accuracy: 0.9792 - scaled_adversarial_loss: 0.0817 - val_loss: 0.0926 - val_sparse_categorical_crossentropy: 0.0447 - val_sparse_categorical_accuracy: 0.9811 - val_scaled_adversarial_loss: 0.0478\n",
      "Epoch 259/1000\n",
      "12/12 [==============================] - 4s 335ms/step - loss: 0.1459 - sparse_categorical_crossentropy: 0.0645 - sparse_categorical_accuracy: 0.9788 - scaled_adversarial_loss: 0.0814 - val_loss: 0.0881 - val_sparse_categorical_crossentropy: 0.0419 - val_sparse_categorical_accuracy: 0.9874 - val_scaled_adversarial_loss: 0.0462\n",
      "Epoch 260/1000\n",
      "12/12 [==============================] - 4s 336ms/step - loss: 0.1456 - sparse_categorical_crossentropy: 0.0630 - sparse_categorical_accuracy: 0.9788 - scaled_adversarial_loss: 0.0826 - val_loss: 0.1111 - val_sparse_categorical_crossentropy: 0.0470 - val_sparse_categorical_accuracy: 0.9874 - val_scaled_adversarial_loss: 0.0641\n",
      "Epoch 261/1000\n",
      "12/12 [==============================] - 4s 335ms/step - loss: 0.1423 - sparse_categorical_crossentropy: 0.0619 - sparse_categorical_accuracy: 0.9788 - scaled_adversarial_loss: 0.0804 - val_loss: 0.0956 - val_sparse_categorical_crossentropy: 0.0417 - val_sparse_categorical_accuracy: 0.9888 - val_scaled_adversarial_loss: 0.0539\n",
      "Epoch 262/1000\n",
      "12/12 [==============================] - 4s 336ms/step - loss: 0.1320 - sparse_categorical_crossentropy: 0.0560 - sparse_categorical_accuracy: 0.9797 - scaled_adversarial_loss: 0.0760 - val_loss: 0.0921 - val_sparse_categorical_crossentropy: 0.0407 - val_sparse_categorical_accuracy: 0.9874 - val_scaled_adversarial_loss: 0.0514\n",
      "Epoch 263/1000\n",
      "12/12 [==============================] - 4s 334ms/step - loss: 0.1316 - sparse_categorical_crossentropy: 0.0564 - sparse_categorical_accuracy: 0.9788 - scaled_adversarial_loss: 0.0752 - val_loss: 0.0861 - val_sparse_categorical_crossentropy: 0.0384 - val_sparse_categorical_accuracy: 0.9895 - val_scaled_adversarial_loss: 0.0477\n",
      "Epoch 264/1000\n",
      "12/12 [==============================] - 4s 362ms/step - loss: 0.1477 - sparse_categorical_crossentropy: 0.0684 - sparse_categorical_accuracy: 0.9769 - scaled_adversarial_loss: 0.0793 - val_loss: 0.0923 - val_sparse_categorical_crossentropy: 0.0440 - val_sparse_categorical_accuracy: 0.9867 - val_scaled_adversarial_loss: 0.0483\n",
      "Epoch 265/1000\n",
      "12/12 [==============================] - 4s 354ms/step - loss: 0.1373 - sparse_categorical_crossentropy: 0.0583 - sparse_categorical_accuracy: 0.9774 - scaled_adversarial_loss: 0.0789 - val_loss: 0.0951 - val_sparse_categorical_crossentropy: 0.0406 - val_sparse_categorical_accuracy: 0.9902 - val_scaled_adversarial_loss: 0.0545\n",
      "Epoch 266/1000\n",
      "12/12 [==============================] - 4s 350ms/step - loss: 0.1409 - sparse_categorical_crossentropy: 0.0619 - sparse_categorical_accuracy: 0.9774 - scaled_adversarial_loss: 0.0790 - val_loss: 0.1015 - val_sparse_categorical_crossentropy: 0.0484 - val_sparse_categorical_accuracy: 0.9839 - val_scaled_adversarial_loss: 0.0531\n",
      "Epoch 267/1000\n",
      "12/12 [==============================] - 4s 352ms/step - loss: 0.1430 - sparse_categorical_crossentropy: 0.0620 - sparse_categorical_accuracy: 0.9811 - scaled_adversarial_loss: 0.0810 - val_loss: 0.0954 - val_sparse_categorical_crossentropy: 0.0442 - val_sparse_categorical_accuracy: 0.9895 - val_scaled_adversarial_loss: 0.0512\n",
      "Epoch 268/1000\n",
      "12/12 [==============================] - 4s 350ms/step - loss: 0.1377 - sparse_categorical_crossentropy: 0.0574 - sparse_categorical_accuracy: 0.9806 - scaled_adversarial_loss: 0.0803 - val_loss: 0.0982 - val_sparse_categorical_crossentropy: 0.0529 - val_sparse_categorical_accuracy: 0.9867 - val_scaled_adversarial_loss: 0.0454\n",
      "Epoch 269/1000\n",
      "12/12 [==============================] - 4s 343ms/step - loss: 0.1393 - sparse_categorical_crossentropy: 0.0593 - sparse_categorical_accuracy: 0.9774 - scaled_adversarial_loss: 0.0800 - val_loss: 0.0981 - val_sparse_categorical_crossentropy: 0.0450 - val_sparse_categorical_accuracy: 0.9860 - val_scaled_adversarial_loss: 0.0531\n",
      "Epoch 270/1000\n",
      "12/12 [==============================] - 4s 330ms/step - loss: 0.1292 - sparse_categorical_crossentropy: 0.0533 - sparse_categorical_accuracy: 0.9823 - scaled_adversarial_loss: 0.0759 - val_loss: 0.0884 - val_sparse_categorical_crossentropy: 0.0400 - val_sparse_categorical_accuracy: 0.9888 - val_scaled_adversarial_loss: 0.0483\n",
      "Epoch 271/1000\n",
      "12/12 [==============================] - 4s 332ms/step - loss: 0.1377 - sparse_categorical_crossentropy: 0.0612 - sparse_categorical_accuracy: 0.9783 - scaled_adversarial_loss: 0.0765 - val_loss: 0.1146 - val_sparse_categorical_crossentropy: 0.0608 - val_sparse_categorical_accuracy: 0.9797 - val_scaled_adversarial_loss: 0.0538\n",
      "Epoch 272/1000\n",
      "12/12 [==============================] - 4s 335ms/step - loss: 0.1456 - sparse_categorical_crossentropy: 0.0673 - sparse_categorical_accuracy: 0.9759 - scaled_adversarial_loss: 0.0783 - val_loss: 0.0973 - val_sparse_categorical_crossentropy: 0.0416 - val_sparse_categorical_accuracy: 0.9853 - val_scaled_adversarial_loss: 0.0557\n",
      "Epoch 273/1000\n",
      "12/12 [==============================] - 4s 343ms/step - loss: 0.1423 - sparse_categorical_crossentropy: 0.0596 - sparse_categorical_accuracy: 0.9783 - scaled_adversarial_loss: 0.0826 - val_loss: 0.0989 - val_sparse_categorical_crossentropy: 0.0456 - val_sparse_categorical_accuracy: 0.9860 - val_scaled_adversarial_loss: 0.0534\n",
      "Epoch 274/1000\n",
      "12/12 [==============================] - 4s 346ms/step - loss: 0.1425 - sparse_categorical_crossentropy: 0.0643 - sparse_categorical_accuracy: 0.9771 - scaled_adversarial_loss: 0.0782 - val_loss: 0.1036 - val_sparse_categorical_crossentropy: 0.0506 - val_sparse_categorical_accuracy: 0.9825 - val_scaled_adversarial_loss: 0.0530\n",
      "Epoch 275/1000\n",
      "12/12 [==============================] - 4s 329ms/step - loss: 0.1572 - sparse_categorical_crossentropy: 0.0714 - sparse_categorical_accuracy: 0.9725 - scaled_adversarial_loss: 0.0859 - val_loss: 0.1013 - val_sparse_categorical_crossentropy: 0.0441 - val_sparse_categorical_accuracy: 0.9832 - val_scaled_adversarial_loss: 0.0572\n",
      "Epoch 276/1000\n",
      "12/12 [==============================] - 4s 371ms/step - loss: 0.1470 - sparse_categorical_crossentropy: 0.0617 - sparse_categorical_accuracy: 0.9788 - scaled_adversarial_loss: 0.0853 - val_loss: 0.0934 - val_sparse_categorical_crossentropy: 0.0428 - val_sparse_categorical_accuracy: 0.9881 - val_scaled_adversarial_loss: 0.0506\n",
      "Epoch 277/1000\n",
      "12/12 [==============================] - 4s 343ms/step - loss: 0.1348 - sparse_categorical_crossentropy: 0.0548 - sparse_categorical_accuracy: 0.9809 - scaled_adversarial_loss: 0.0799 - val_loss: 0.0834 - val_sparse_categorical_crossentropy: 0.0409 - val_sparse_categorical_accuracy: 0.9881 - val_scaled_adversarial_loss: 0.0425\n",
      "Epoch 278/1000\n",
      "12/12 [==============================] - 4s 345ms/step - loss: 0.1234 - sparse_categorical_crossentropy: 0.0491 - sparse_categorical_accuracy: 0.9822 - scaled_adversarial_loss: 0.0743 - val_loss: 0.0928 - val_sparse_categorical_crossentropy: 0.0424 - val_sparse_categorical_accuracy: 0.9860 - val_scaled_adversarial_loss: 0.0504\n",
      "Epoch 279/1000\n",
      "12/12 [==============================] - 4s 357ms/step - loss: 0.1335 - sparse_categorical_crossentropy: 0.0569 - sparse_categorical_accuracy: 0.9816 - scaled_adversarial_loss: 0.0765 - val_loss: 0.1014 - val_sparse_categorical_crossentropy: 0.0430 - val_sparse_categorical_accuracy: 0.9839 - val_scaled_adversarial_loss: 0.0583\n",
      "Epoch 280/1000\n",
      "12/12 [==============================] - 4s 346ms/step - loss: 0.1389 - sparse_categorical_crossentropy: 0.0546 - sparse_categorical_accuracy: 0.9811 - scaled_adversarial_loss: 0.0843 - val_loss: 0.0953 - val_sparse_categorical_crossentropy: 0.0467 - val_sparse_categorical_accuracy: 0.9832 - val_scaled_adversarial_loss: 0.0485\n",
      "Epoch 281/1000\n",
      "12/12 [==============================] - 4s 344ms/step - loss: 0.1375 - sparse_categorical_crossentropy: 0.0623 - sparse_categorical_accuracy: 0.9790 - scaled_adversarial_loss: 0.0752 - val_loss: 0.1004 - val_sparse_categorical_crossentropy: 0.0460 - val_sparse_categorical_accuracy: 0.9832 - val_scaled_adversarial_loss: 0.0544\n",
      "Epoch 282/1000\n",
      "12/12 [==============================] - 4s 348ms/step - loss: 0.1352 - sparse_categorical_crossentropy: 0.0574 - sparse_categorical_accuracy: 0.9802 - scaled_adversarial_loss: 0.0778 - val_loss: 0.1061 - val_sparse_categorical_crossentropy: 0.0628 - val_sparse_categorical_accuracy: 0.9762 - val_scaled_adversarial_loss: 0.0433\n",
      "Epoch 283/1000\n",
      "12/12 [==============================] - 4s 360ms/step - loss: 0.1394 - sparse_categorical_crossentropy: 0.0634 - sparse_categorical_accuracy: 0.9771 - scaled_adversarial_loss: 0.0760 - val_loss: 0.0877 - val_sparse_categorical_crossentropy: 0.0430 - val_sparse_categorical_accuracy: 0.9832 - val_scaled_adversarial_loss: 0.0447\n",
      "Epoch 284/1000\n",
      "12/12 [==============================] - 4s 346ms/step - loss: 0.1453 - sparse_categorical_crossentropy: 0.0627 - sparse_categorical_accuracy: 0.9766 - scaled_adversarial_loss: 0.0825 - val_loss: 0.0968 - val_sparse_categorical_crossentropy: 0.0395 - val_sparse_categorical_accuracy: 0.9888 - val_scaled_adversarial_loss: 0.0573\n",
      "Epoch 285/1000\n",
      "12/12 [==============================] - 4s 338ms/step - loss: 0.1265 - sparse_categorical_crossentropy: 0.0520 - sparse_categorical_accuracy: 0.9808 - scaled_adversarial_loss: 0.0745 - val_loss: 0.0804 - val_sparse_categorical_crossentropy: 0.0381 - val_sparse_categorical_accuracy: 0.9874 - val_scaled_adversarial_loss: 0.0423\n",
      "Epoch 286/1000\n",
      "12/12 [==============================] - 4s 359ms/step - loss: 0.1322 - sparse_categorical_crossentropy: 0.0550 - sparse_categorical_accuracy: 0.9804 - scaled_adversarial_loss: 0.0772 - val_loss: 0.0953 - val_sparse_categorical_crossentropy: 0.0409 - val_sparse_categorical_accuracy: 0.9860 - val_scaled_adversarial_loss: 0.0545\n",
      "Epoch 287/1000\n",
      "12/12 [==============================] - 4s 329ms/step - loss: 0.1373 - sparse_categorical_crossentropy: 0.0597 - sparse_categorical_accuracy: 0.9792 - scaled_adversarial_loss: 0.0777 - val_loss: 0.0885 - val_sparse_categorical_crossentropy: 0.0398 - val_sparse_categorical_accuracy: 0.9895 - val_scaled_adversarial_loss: 0.0488\n",
      "Epoch 288/1000\n",
      "12/12 [==============================] - 4s 353ms/step - loss: 0.1427 - sparse_categorical_crossentropy: 0.0681 - sparse_categorical_accuracy: 0.9760 - scaled_adversarial_loss: 0.0746 - val_loss: 0.0901 - val_sparse_categorical_crossentropy: 0.0420 - val_sparse_categorical_accuracy: 0.9825 - val_scaled_adversarial_loss: 0.0481\n",
      "Epoch 289/1000\n",
      "12/12 [==============================] - 4s 363ms/step - loss: 0.1278 - sparse_categorical_crossentropy: 0.0545 - sparse_categorical_accuracy: 0.9815 - scaled_adversarial_loss: 0.0733 - val_loss: 0.0874 - val_sparse_categorical_crossentropy: 0.0394 - val_sparse_categorical_accuracy: 0.9888 - val_scaled_adversarial_loss: 0.0480\n",
      "Epoch 290/1000\n",
      "12/12 [==============================] - 4s 348ms/step - loss: 0.1283 - sparse_categorical_crossentropy: 0.0577 - sparse_categorical_accuracy: 0.9816 - scaled_adversarial_loss: 0.0706 - val_loss: 0.0919 - val_sparse_categorical_crossentropy: 0.0393 - val_sparse_categorical_accuracy: 0.9881 - val_scaled_adversarial_loss: 0.0526\n",
      "Epoch 291/1000\n",
      "12/12 [==============================] - 4s 350ms/step - loss: 0.1362 - sparse_categorical_crossentropy: 0.0576 - sparse_categorical_accuracy: 0.9820 - scaled_adversarial_loss: 0.0785 - val_loss: 0.0981 - val_sparse_categorical_crossentropy: 0.0450 - val_sparse_categorical_accuracy: 0.9825 - val_scaled_adversarial_loss: 0.0531\n",
      "Epoch 292/1000\n",
      "12/12 [==============================] - 4s 347ms/step - loss: 0.1408 - sparse_categorical_crossentropy: 0.0569 - sparse_categorical_accuracy: 0.9794 - scaled_adversarial_loss: 0.0840 - val_loss: 0.1034 - val_sparse_categorical_crossentropy: 0.0392 - val_sparse_categorical_accuracy: 0.9881 - val_scaled_adversarial_loss: 0.0642\n",
      "Epoch 293/1000\n",
      "12/12 [==============================] - 4s 343ms/step - loss: 0.1520 - sparse_categorical_crossentropy: 0.0692 - sparse_categorical_accuracy: 0.9780 - scaled_adversarial_loss: 0.0828 - val_loss: 0.0921 - val_sparse_categorical_crossentropy: 0.0446 - val_sparse_categorical_accuracy: 0.9846 - val_scaled_adversarial_loss: 0.0475\n",
      "Epoch 294/1000\n",
      "12/12 [==============================] - 4s 339ms/step - loss: 0.1411 - sparse_categorical_crossentropy: 0.0620 - sparse_categorical_accuracy: 0.9780 - scaled_adversarial_loss: 0.0791 - val_loss: 0.0884 - val_sparse_categorical_crossentropy: 0.0417 - val_sparse_categorical_accuracy: 0.9860 - val_scaled_adversarial_loss: 0.0467\n",
      "Epoch 295/1000\n",
      "12/12 [==============================] - 4s 338ms/step - loss: 0.1305 - sparse_categorical_crossentropy: 0.0552 - sparse_categorical_accuracy: 0.9809 - scaled_adversarial_loss: 0.0753 - val_loss: 0.1016 - val_sparse_categorical_crossentropy: 0.0419 - val_sparse_categorical_accuracy: 0.9846 - val_scaled_adversarial_loss: 0.0597\n",
      "Epoch 296/1000\n",
      "12/12 [==============================] - 4s 339ms/step - loss: 0.1419 - sparse_categorical_crossentropy: 0.0595 - sparse_categorical_accuracy: 0.9792 - scaled_adversarial_loss: 0.0824 - val_loss: 0.0865 - val_sparse_categorical_crossentropy: 0.0402 - val_sparse_categorical_accuracy: 0.9853 - val_scaled_adversarial_loss: 0.0463\n",
      "Epoch 297/1000\n",
      "12/12 [==============================] - 4s 337ms/step - loss: 0.1324 - sparse_categorical_crossentropy: 0.0533 - sparse_categorical_accuracy: 0.9834 - scaled_adversarial_loss: 0.0792 - val_loss: 0.1064 - val_sparse_categorical_crossentropy: 0.0533 - val_sparse_categorical_accuracy: 0.9825 - val_scaled_adversarial_loss: 0.0531\n",
      "Epoch 298/1000\n",
      "12/12 [==============================] - 4s 339ms/step - loss: 0.1401 - sparse_categorical_crossentropy: 0.0600 - sparse_categorical_accuracy: 0.9799 - scaled_adversarial_loss: 0.0801 - val_loss: 0.1116 - val_sparse_categorical_crossentropy: 0.0486 - val_sparse_categorical_accuracy: 0.9818 - val_scaled_adversarial_loss: 0.0630\n",
      "Epoch 299/1000\n",
      "12/12 [==============================] - 4s 338ms/step - loss: 0.1417 - sparse_categorical_crossentropy: 0.0662 - sparse_categorical_accuracy: 0.9794 - scaled_adversarial_loss: 0.0756 - val_loss: 0.1241 - val_sparse_categorical_crossentropy: 0.0577 - val_sparse_categorical_accuracy: 0.9832 - val_scaled_adversarial_loss: 0.0664\n",
      "Epoch 300/1000\n",
      "12/12 [==============================] - 4s 337ms/step - loss: 0.1607 - sparse_categorical_crossentropy: 0.0769 - sparse_categorical_accuracy: 0.9755 - scaled_adversarial_loss: 0.0838 - val_loss: 0.0998 - val_sparse_categorical_crossentropy: 0.0456 - val_sparse_categorical_accuracy: 0.9881 - val_scaled_adversarial_loss: 0.0542\n",
      "Epoch 301/1000\n",
      "12/12 [==============================] - 4s 336ms/step - loss: 0.1465 - sparse_categorical_crossentropy: 0.0633 - sparse_categorical_accuracy: 0.9811 - scaled_adversarial_loss: 0.0832 - val_loss: 0.0935 - val_sparse_categorical_crossentropy: 0.0442 - val_sparse_categorical_accuracy: 0.9867 - val_scaled_adversarial_loss: 0.0493\n",
      "Epoch 302/1000\n",
      "12/12 [==============================] - 4s 337ms/step - loss: 0.1425 - sparse_categorical_crossentropy: 0.0661 - sparse_categorical_accuracy: 0.9760 - scaled_adversarial_loss: 0.0764 - val_loss: 0.1062 - val_sparse_categorical_crossentropy: 0.0520 - val_sparse_categorical_accuracy: 0.9832 - val_scaled_adversarial_loss: 0.0542\n",
      "Epoch 303/1000\n",
      "12/12 [==============================] - 4s 337ms/step - loss: 0.1452 - sparse_categorical_crossentropy: 0.0621 - sparse_categorical_accuracy: 0.9778 - scaled_adversarial_loss: 0.0831 - val_loss: 0.0957 - val_sparse_categorical_crossentropy: 0.0411 - val_sparse_categorical_accuracy: 0.9867 - val_scaled_adversarial_loss: 0.0546\n",
      "Epoch 304/1000\n",
      "12/12 [==============================] - 4s 340ms/step - loss: 0.1373 - sparse_categorical_crossentropy: 0.0513 - sparse_categorical_accuracy: 0.9809 - scaled_adversarial_loss: 0.0860 - val_loss: 0.0904 - val_sparse_categorical_crossentropy: 0.0407 - val_sparse_categorical_accuracy: 0.9867 - val_scaled_adversarial_loss: 0.0496\n",
      "Epoch 305/1000\n",
      "12/12 [==============================] - 4s 350ms/step - loss: 0.1224 - sparse_categorical_crossentropy: 0.0474 - sparse_categorical_accuracy: 0.9837 - scaled_adversarial_loss: 0.0750 - val_loss: 0.0971 - val_sparse_categorical_crossentropy: 0.0501 - val_sparse_categorical_accuracy: 0.9874 - val_scaled_adversarial_loss: 0.0470\n",
      "Epoch 306/1000\n",
      "12/12 [==============================] - 4s 336ms/step - loss: 0.1348 - sparse_categorical_crossentropy: 0.0555 - sparse_categorical_accuracy: 0.9806 - scaled_adversarial_loss: 0.0793 - val_loss: 0.0929 - val_sparse_categorical_crossentropy: 0.0386 - val_sparse_categorical_accuracy: 0.9909 - val_scaled_adversarial_loss: 0.0543\n",
      "Epoch 307/1000\n",
      "12/12 [==============================] - 4s 340ms/step - loss: 0.1306 - sparse_categorical_crossentropy: 0.0563 - sparse_categorical_accuracy: 0.9804 - scaled_adversarial_loss: 0.0744 - val_loss: 0.1043 - val_sparse_categorical_crossentropy: 0.0435 - val_sparse_categorical_accuracy: 0.9832 - val_scaled_adversarial_loss: 0.0609\n",
      "Epoch 308/1000\n",
      "12/12 [==============================] - 4s 338ms/step - loss: 0.1360 - sparse_categorical_crossentropy: 0.0575 - sparse_categorical_accuracy: 0.9776 - scaled_adversarial_loss: 0.0785 - val_loss: 0.0922 - val_sparse_categorical_crossentropy: 0.0394 - val_sparse_categorical_accuracy: 0.9867 - val_scaled_adversarial_loss: 0.0527\n",
      "Epoch 309/1000\n",
      "12/12 [==============================] - 4s 334ms/step - loss: 0.1267 - sparse_categorical_crossentropy: 0.0510 - sparse_categorical_accuracy: 0.9811 - scaled_adversarial_loss: 0.0757 - val_loss: 0.0902 - val_sparse_categorical_crossentropy: 0.0435 - val_sparse_categorical_accuracy: 0.9867 - val_scaled_adversarial_loss: 0.0467\n",
      "Epoch 310/1000\n",
      "12/12 [==============================] - 4s 344ms/step - loss: 0.1417 - sparse_categorical_crossentropy: 0.0644 - sparse_categorical_accuracy: 0.9781 - scaled_adversarial_loss: 0.0773 - val_loss: 0.0815 - val_sparse_categorical_crossentropy: 0.0441 - val_sparse_categorical_accuracy: 0.9874 - val_scaled_adversarial_loss: 0.0374\n",
      "Epoch 311/1000\n",
      "12/12 [==============================] - 4s 328ms/step - loss: 0.1317 - sparse_categorical_crossentropy: 0.0512 - sparse_categorical_accuracy: 0.9818 - scaled_adversarial_loss: 0.0804 - val_loss: 0.0883 - val_sparse_categorical_crossentropy: 0.0461 - val_sparse_categorical_accuracy: 0.9881 - val_scaled_adversarial_loss: 0.0422\n",
      "Epoch 312/1000\n",
      "12/12 [==============================] - 4s 340ms/step - loss: 0.1273 - sparse_categorical_crossentropy: 0.0542 - sparse_categorical_accuracy: 0.9811 - scaled_adversarial_loss: 0.0732 - val_loss: 0.0802 - val_sparse_categorical_crossentropy: 0.0379 - val_sparse_categorical_accuracy: 0.9874 - val_scaled_adversarial_loss: 0.0423\n",
      "Epoch 313/1000\n",
      "12/12 [==============================] - 4s 329ms/step - loss: 0.1368 - sparse_categorical_crossentropy: 0.0580 - sparse_categorical_accuracy: 0.9799 - scaled_adversarial_loss: 0.0789 - val_loss: 0.1042 - val_sparse_categorical_crossentropy: 0.0467 - val_sparse_categorical_accuracy: 0.9832 - val_scaled_adversarial_loss: 0.0575\n",
      "Epoch 314/1000\n",
      "12/12 [==============================] - 4s 341ms/step - loss: 0.1234 - sparse_categorical_crossentropy: 0.0520 - sparse_categorical_accuracy: 0.9816 - scaled_adversarial_loss: 0.0714 - val_loss: 0.0885 - val_sparse_categorical_crossentropy: 0.0388 - val_sparse_categorical_accuracy: 0.9881 - val_scaled_adversarial_loss: 0.0497\n",
      "Epoch 315/1000\n",
      "12/12 [==============================] - 4s 346ms/step - loss: 0.1252 - sparse_categorical_crossentropy: 0.0521 - sparse_categorical_accuracy: 0.9832 - scaled_adversarial_loss: 0.0732 - val_loss: 0.0987 - val_sparse_categorical_crossentropy: 0.0374 - val_sparse_categorical_accuracy: 0.9888 - val_scaled_adversarial_loss: 0.0613\n",
      "Epoch 316/1000\n",
      "12/12 [==============================] - 4s 370ms/step - loss: 0.1239 - sparse_categorical_crossentropy: 0.0490 - sparse_categorical_accuracy: 0.9834 - scaled_adversarial_loss: 0.0749 - val_loss: 0.0879 - val_sparse_categorical_crossentropy: 0.0373 - val_sparse_categorical_accuracy: 0.9860 - val_scaled_adversarial_loss: 0.0507\n",
      "Epoch 317/1000\n",
      "12/12 [==============================] - 4s 365ms/step - loss: 0.1367 - sparse_categorical_crossentropy: 0.0615 - sparse_categorical_accuracy: 0.9813 - scaled_adversarial_loss: 0.0752 - val_loss: 0.0956 - val_sparse_categorical_crossentropy: 0.0444 - val_sparse_categorical_accuracy: 0.9881 - val_scaled_adversarial_loss: 0.0512\n",
      "Epoch 318/1000\n",
      "12/12 [==============================] - 4s 339ms/step - loss: 0.1255 - sparse_categorical_crossentropy: 0.0516 - sparse_categorical_accuracy: 0.9836 - scaled_adversarial_loss: 0.0739 - val_loss: 0.0917 - val_sparse_categorical_crossentropy: 0.0400 - val_sparse_categorical_accuracy: 0.9888 - val_scaled_adversarial_loss: 0.0517\n",
      "Epoch 319/1000\n",
      "12/12 [==============================] - 4s 354ms/step - loss: 0.1289 - sparse_categorical_crossentropy: 0.0482 - sparse_categorical_accuracy: 0.9815 - scaled_adversarial_loss: 0.0807 - val_loss: 0.1067 - val_sparse_categorical_crossentropy: 0.0453 - val_sparse_categorical_accuracy: 0.9867 - val_scaled_adversarial_loss: 0.0615\n",
      "Epoch 320/1000\n",
      "12/12 [==============================] - 4s 364ms/step - loss: 0.1329 - sparse_categorical_crossentropy: 0.0555 - sparse_categorical_accuracy: 0.9804 - scaled_adversarial_loss: 0.0774 - val_loss: 0.0978 - val_sparse_categorical_crossentropy: 0.0538 - val_sparse_categorical_accuracy: 0.9853 - val_scaled_adversarial_loss: 0.0440\n",
      "Epoch 321/1000\n",
      "12/12 [==============================] - 4s 334ms/step - loss: 0.1420 - sparse_categorical_crossentropy: 0.0588 - sparse_categorical_accuracy: 0.9801 - scaled_adversarial_loss: 0.0832 - val_loss: 0.0900 - val_sparse_categorical_crossentropy: 0.0486 - val_sparse_categorical_accuracy: 0.9860 - val_scaled_adversarial_loss: 0.0414\n",
      "Epoch 322/1000\n",
      "12/12 [==============================] - 4s 352ms/step - loss: 0.1616 - sparse_categorical_crossentropy: 0.0763 - sparse_categorical_accuracy: 0.9727 - scaled_adversarial_loss: 0.0853 - val_loss: 0.0967 - val_sparse_categorical_crossentropy: 0.0421 - val_sparse_categorical_accuracy: 0.9867 - val_scaled_adversarial_loss: 0.0546\n",
      "Epoch 323/1000\n",
      "12/12 [==============================] - 4s 332ms/step - loss: 0.1459 - sparse_categorical_crossentropy: 0.0610 - sparse_categorical_accuracy: 0.9788 - scaled_adversarial_loss: 0.0849 - val_loss: 0.0971 - val_sparse_categorical_crossentropy: 0.0396 - val_sparse_categorical_accuracy: 0.9860 - val_scaled_adversarial_loss: 0.0575\n",
      "Epoch 324/1000\n",
      "12/12 [==============================] - 4s 323ms/step - loss: 0.1391 - sparse_categorical_crossentropy: 0.0544 - sparse_categorical_accuracy: 0.9802 - scaled_adversarial_loss: 0.0847 - val_loss: 0.0922 - val_sparse_categorical_crossentropy: 0.0478 - val_sparse_categorical_accuracy: 0.9790 - val_scaled_adversarial_loss: 0.0444\n",
      "Epoch 325/1000\n",
      "12/12 [==============================] - 4s 332ms/step - loss: 0.1419 - sparse_categorical_crossentropy: 0.0628 - sparse_categorical_accuracy: 0.9795 - scaled_adversarial_loss: 0.0791 - val_loss: 0.0906 - val_sparse_categorical_crossentropy: 0.0425 - val_sparse_categorical_accuracy: 0.9867 - val_scaled_adversarial_loss: 0.0481\n",
      "Epoch 326/1000\n",
      "12/12 [==============================] - 5s 396ms/step - loss: 0.1369 - sparse_categorical_crossentropy: 0.0586 - sparse_categorical_accuracy: 0.9802 - scaled_adversarial_loss: 0.0783 - val_loss: 0.0825 - val_sparse_categorical_crossentropy: 0.0370 - val_sparse_categorical_accuracy: 0.9867 - val_scaled_adversarial_loss: 0.0455\n",
      "Epoch 327/1000\n",
      "12/12 [==============================] - 4s 361ms/step - loss: 0.1311 - sparse_categorical_crossentropy: 0.0459 - sparse_categorical_accuracy: 0.9836 - scaled_adversarial_loss: 0.0852 - val_loss: 0.0954 - val_sparse_categorical_crossentropy: 0.0425 - val_sparse_categorical_accuracy: 0.9867 - val_scaled_adversarial_loss: 0.0528\n",
      "Epoch 328/1000\n",
      "12/12 [==============================] - 4s 354ms/step - loss: 0.1348 - sparse_categorical_crossentropy: 0.0544 - sparse_categorical_accuracy: 0.9839 - scaled_adversarial_loss: 0.0805 - val_loss: 0.0986 - val_sparse_categorical_crossentropy: 0.0391 - val_sparse_categorical_accuracy: 0.9881 - val_scaled_adversarial_loss: 0.0595\n",
      "Epoch 329/1000\n",
      "12/12 [==============================] - 4s 333ms/step - loss: 0.1389 - sparse_categorical_crossentropy: 0.0578 - sparse_categorical_accuracy: 0.9822 - scaled_adversarial_loss: 0.0811 - val_loss: 0.0885 - val_sparse_categorical_crossentropy: 0.0366 - val_sparse_categorical_accuracy: 0.9888 - val_scaled_adversarial_loss: 0.0519\n",
      "Epoch 330/1000\n",
      "12/12 [==============================] - 4s 337ms/step - loss: 0.1258 - sparse_categorical_crossentropy: 0.0496 - sparse_categorical_accuracy: 0.9815 - scaled_adversarial_loss: 0.0762 - val_loss: 0.0871 - val_sparse_categorical_crossentropy: 0.0382 - val_sparse_categorical_accuracy: 0.9860 - val_scaled_adversarial_loss: 0.0489\n",
      "Epoch 331/1000\n",
      "12/12 [==============================] - 4s 332ms/step - loss: 0.1359 - sparse_categorical_crossentropy: 0.0523 - sparse_categorical_accuracy: 0.9830 - scaled_adversarial_loss: 0.0836 - val_loss: 0.1025 - val_sparse_categorical_crossentropy: 0.0378 - val_sparse_categorical_accuracy: 0.9832 - val_scaled_adversarial_loss: 0.0647\n",
      "Epoch 332/1000\n",
      "12/12 [==============================] - 5s 388ms/step - loss: 0.1334 - sparse_categorical_crossentropy: 0.0519 - sparse_categorical_accuracy: 0.9816 - scaled_adversarial_loss: 0.0815 - val_loss: 0.1074 - val_sparse_categorical_crossentropy: 0.0541 - val_sparse_categorical_accuracy: 0.9867 - val_scaled_adversarial_loss: 0.0533\n",
      "Epoch 333/1000\n",
      "12/12 [==============================] - 5s 387ms/step - loss: 0.1339 - sparse_categorical_crossentropy: 0.0537 - sparse_categorical_accuracy: 0.9797 - scaled_adversarial_loss: 0.0801 - val_loss: 0.0984 - val_sparse_categorical_crossentropy: 0.0438 - val_sparse_categorical_accuracy: 0.9853 - val_scaled_adversarial_loss: 0.0546\n",
      "Epoch 334/1000\n",
      "12/12 [==============================] - 5s 389ms/step - loss: 0.1435 - sparse_categorical_crossentropy: 0.0576 - sparse_categorical_accuracy: 0.9801 - scaled_adversarial_loss: 0.0859 - val_loss: 0.0896 - val_sparse_categorical_crossentropy: 0.0433 - val_sparse_categorical_accuracy: 0.9860 - val_scaled_adversarial_loss: 0.0463\n",
      "Epoch 335/1000\n",
      "12/12 [==============================] - 5s 420ms/step - loss: 0.1281 - sparse_categorical_crossentropy: 0.0511 - sparse_categorical_accuracy: 0.9827 - scaled_adversarial_loss: 0.0770 - val_loss: 0.0979 - val_sparse_categorical_crossentropy: 0.0428 - val_sparse_categorical_accuracy: 0.9853 - val_scaled_adversarial_loss: 0.0551\n",
      "Epoch 336/1000\n",
      "12/12 [==============================] - 5s 403ms/step - loss: 0.1375 - sparse_categorical_crossentropy: 0.0581 - sparse_categorical_accuracy: 0.9811 - scaled_adversarial_loss: 0.0794 - val_loss: 0.0776 - val_sparse_categorical_crossentropy: 0.0377 - val_sparse_categorical_accuracy: 0.9874 - val_scaled_adversarial_loss: 0.0399\n",
      "Epoch 337/1000\n",
      "12/12 [==============================] - 5s 403ms/step - loss: 0.1418 - sparse_categorical_crossentropy: 0.0551 - sparse_categorical_accuracy: 0.9801 - scaled_adversarial_loss: 0.0867 - val_loss: 0.1018 - val_sparse_categorical_crossentropy: 0.0415 - val_sparse_categorical_accuracy: 0.9874 - val_scaled_adversarial_loss: 0.0603\n",
      "Epoch 338/1000\n",
      "12/12 [==============================] - 5s 393ms/step - loss: 0.1352 - sparse_categorical_crossentropy: 0.0561 - sparse_categorical_accuracy: 0.9797 - scaled_adversarial_loss: 0.0791 - val_loss: 0.0924 - val_sparse_categorical_crossentropy: 0.0467 - val_sparse_categorical_accuracy: 0.9874 - val_scaled_adversarial_loss: 0.0457\n",
      "Epoch 339/1000\n",
      "12/12 [==============================] - 5s 415ms/step - loss: 0.1319 - sparse_categorical_crossentropy: 0.0566 - sparse_categorical_accuracy: 0.9820 - scaled_adversarial_loss: 0.0753 - val_loss: 0.1201 - val_sparse_categorical_crossentropy: 0.0577 - val_sparse_categorical_accuracy: 0.9811 - val_scaled_adversarial_loss: 0.0624\n",
      "Epoch 340/1000\n",
      "12/12 [==============================] - 5s 387ms/step - loss: 0.1438 - sparse_categorical_crossentropy: 0.0576 - sparse_categorical_accuracy: 0.9790 - scaled_adversarial_loss: 0.0862 - val_loss: 0.1342 - val_sparse_categorical_crossentropy: 0.0651 - val_sparse_categorical_accuracy: 0.9762 - val_scaled_adversarial_loss: 0.0691\n",
      "Epoch 341/1000\n",
      "12/12 [==============================] - 4s 371ms/step - loss: 0.1476 - sparse_categorical_crossentropy: 0.0624 - sparse_categorical_accuracy: 0.9792 - scaled_adversarial_loss: 0.0851 - val_loss: 0.0849 - val_sparse_categorical_crossentropy: 0.0386 - val_sparse_categorical_accuracy: 0.9888 - val_scaled_adversarial_loss: 0.0464\n",
      "Epoch 342/1000\n",
      "12/12 [==============================] - 5s 391ms/step - loss: 0.1393 - sparse_categorical_crossentropy: 0.0588 - sparse_categorical_accuracy: 0.9787 - scaled_adversarial_loss: 0.0805 - val_loss: 0.0941 - val_sparse_categorical_crossentropy: 0.0444 - val_sparse_categorical_accuracy: 0.9888 - val_scaled_adversarial_loss: 0.0497\n",
      "Epoch 343/1000\n",
      "12/12 [==============================] - 5s 395ms/step - loss: 0.1292 - sparse_categorical_crossentropy: 0.0510 - sparse_categorical_accuracy: 0.9801 - scaled_adversarial_loss: 0.0782 - val_loss: 0.0989 - val_sparse_categorical_crossentropy: 0.0455 - val_sparse_categorical_accuracy: 0.9867 - val_scaled_adversarial_loss: 0.0534\n",
      "Epoch 344/1000\n",
      "12/12 [==============================] - 4s 371ms/step - loss: 0.1248 - sparse_categorical_crossentropy: 0.0498 - sparse_categorical_accuracy: 0.9843 - scaled_adversarial_loss: 0.0750 - val_loss: 0.0962 - val_sparse_categorical_crossentropy: 0.0406 - val_sparse_categorical_accuracy: 0.9846 - val_scaled_adversarial_loss: 0.0556\n",
      "Epoch 345/1000\n",
      "12/12 [==============================] - 4s 354ms/step - loss: 0.1165 - sparse_categorical_crossentropy: 0.0428 - sparse_categorical_accuracy: 0.9832 - scaled_adversarial_loss: 0.0737 - val_loss: 0.0866 - val_sparse_categorical_crossentropy: 0.0383 - val_sparse_categorical_accuracy: 0.9888 - val_scaled_adversarial_loss: 0.0483\n",
      "Epoch 346/1000\n",
      "12/12 [==============================] - 4s 361ms/step - loss: 0.1284 - sparse_categorical_crossentropy: 0.0493 - sparse_categorical_accuracy: 0.9823 - scaled_adversarial_loss: 0.0792 - val_loss: 0.0897 - val_sparse_categorical_crossentropy: 0.0341 - val_sparse_categorical_accuracy: 0.9888 - val_scaled_adversarial_loss: 0.0556\n",
      "Epoch 347/1000\n",
      "12/12 [==============================] - 5s 410ms/step - loss: 0.1256 - sparse_categorical_crossentropy: 0.0456 - sparse_categorical_accuracy: 0.9851 - scaled_adversarial_loss: 0.0800 - val_loss: 0.0891 - val_sparse_categorical_crossentropy: 0.0365 - val_sparse_categorical_accuracy: 0.9881 - val_scaled_adversarial_loss: 0.0526\n",
      "Epoch 348/1000\n",
      "12/12 [==============================] - 5s 389ms/step - loss: 0.1205 - sparse_categorical_crossentropy: 0.0482 - sparse_categorical_accuracy: 0.9841 - scaled_adversarial_loss: 0.0723 - val_loss: 0.0954 - val_sparse_categorical_crossentropy: 0.0394 - val_sparse_categorical_accuracy: 0.9874 - val_scaled_adversarial_loss: 0.0559\n",
      "Epoch 349/1000\n",
      "12/12 [==============================] - 5s 383ms/step - loss: 0.1269 - sparse_categorical_crossentropy: 0.0492 - sparse_categorical_accuracy: 0.9830 - scaled_adversarial_loss: 0.0778 - val_loss: 0.0854 - val_sparse_categorical_crossentropy: 0.0383 - val_sparse_categorical_accuracy: 0.9888 - val_scaled_adversarial_loss: 0.0470\n",
      "Epoch 350/1000\n",
      "12/12 [==============================] - 5s 412ms/step - loss: 0.1268 - sparse_categorical_crossentropy: 0.0514 - sparse_categorical_accuracy: 0.9827 - scaled_adversarial_loss: 0.0754 - val_loss: 0.0849 - val_sparse_categorical_crossentropy: 0.0356 - val_sparse_categorical_accuracy: 0.9902 - val_scaled_adversarial_loss: 0.0493\n",
      "Epoch 351/1000\n",
      "12/12 [==============================] - 5s 385ms/step - loss: 0.1267 - sparse_categorical_crossentropy: 0.0511 - sparse_categorical_accuracy: 0.9823 - scaled_adversarial_loss: 0.0756 - val_loss: 0.0850 - val_sparse_categorical_crossentropy: 0.0353 - val_sparse_categorical_accuracy: 0.9902 - val_scaled_adversarial_loss: 0.0498\n",
      "Epoch 352/1000\n",
      "12/12 [==============================] - 4s 369ms/step - loss: 0.1201 - sparse_categorical_crossentropy: 0.0495 - sparse_categorical_accuracy: 0.9820 - scaled_adversarial_loss: 0.0707 - val_loss: 0.0776 - val_sparse_categorical_crossentropy: 0.0388 - val_sparse_categorical_accuracy: 0.9895 - val_scaled_adversarial_loss: 0.0388\n",
      "Epoch 353/1000\n",
      "12/12 [==============================] - 4s 353ms/step - loss: 0.1238 - sparse_categorical_crossentropy: 0.0479 - sparse_categorical_accuracy: 0.9818 - scaled_adversarial_loss: 0.0759 - val_loss: 0.0864 - val_sparse_categorical_crossentropy: 0.0375 - val_sparse_categorical_accuracy: 0.9888 - val_scaled_adversarial_loss: 0.0490\n",
      "Epoch 354/1000\n",
      "12/12 [==============================] - 4s 354ms/step - loss: 0.1230 - sparse_categorical_crossentropy: 0.0466 - sparse_categorical_accuracy: 0.9823 - scaled_adversarial_loss: 0.0763 - val_loss: 0.0975 - val_sparse_categorical_crossentropy: 0.0420 - val_sparse_categorical_accuracy: 0.9860 - val_scaled_adversarial_loss: 0.0555\n",
      "Epoch 355/1000\n",
      "12/12 [==============================] - 4s 336ms/step - loss: 0.1357 - sparse_categorical_crossentropy: 0.0552 - sparse_categorical_accuracy: 0.9809 - scaled_adversarial_loss: 0.0805 - val_loss: 0.0956 - val_sparse_categorical_crossentropy: 0.0446 - val_sparse_categorical_accuracy: 0.9860 - val_scaled_adversarial_loss: 0.0510\n",
      "Epoch 356/1000\n",
      "12/12 [==============================] - 4s 337ms/step - loss: 0.1286 - sparse_categorical_crossentropy: 0.0516 - sparse_categorical_accuracy: 0.9823 - scaled_adversarial_loss: 0.0770 - val_loss: 0.0926 - val_sparse_categorical_crossentropy: 0.0397 - val_sparse_categorical_accuracy: 0.9867 - val_scaled_adversarial_loss: 0.0529\n",
      "Epoch 357/1000\n",
      "12/12 [==============================] - 4s 346ms/step - loss: 0.1310 - sparse_categorical_crossentropy: 0.0552 - sparse_categorical_accuracy: 0.9809 - scaled_adversarial_loss: 0.0757 - val_loss: 0.0848 - val_sparse_categorical_crossentropy: 0.0387 - val_sparse_categorical_accuracy: 0.9888 - val_scaled_adversarial_loss: 0.0461\n",
      "Epoch 358/1000\n",
      "12/12 [==============================] - 4s 330ms/step - loss: 0.1234 - sparse_categorical_crossentropy: 0.0446 - sparse_categorical_accuracy: 0.9829 - scaled_adversarial_loss: 0.0788 - val_loss: 0.0898 - val_sparse_categorical_crossentropy: 0.0374 - val_sparse_categorical_accuracy: 0.9881 - val_scaled_adversarial_loss: 0.0524\n",
      "Epoch 359/1000\n",
      "12/12 [==============================] - 4s 339ms/step - loss: 0.1256 - sparse_categorical_crossentropy: 0.0456 - sparse_categorical_accuracy: 0.9837 - scaled_adversarial_loss: 0.0800 - val_loss: 0.0977 - val_sparse_categorical_crossentropy: 0.0389 - val_sparse_categorical_accuracy: 0.9902 - val_scaled_adversarial_loss: 0.0588\n",
      "Epoch 360/1000\n",
      "12/12 [==============================] - 4s 333ms/step - loss: 0.1249 - sparse_categorical_crossentropy: 0.0489 - sparse_categorical_accuracy: 0.9809 - scaled_adversarial_loss: 0.0760 - val_loss: 0.0969 - val_sparse_categorical_crossentropy: 0.0444 - val_sparse_categorical_accuracy: 0.9874 - val_scaled_adversarial_loss: 0.0524\n",
      "Epoch 361/1000\n",
      "12/12 [==============================] - 4s 332ms/step - loss: 0.1276 - sparse_categorical_crossentropy: 0.0500 - sparse_categorical_accuracy: 0.9834 - scaled_adversarial_loss: 0.0776 - val_loss: 0.1183 - val_sparse_categorical_crossentropy: 0.0477 - val_sparse_categorical_accuracy: 0.9860 - val_scaled_adversarial_loss: 0.0706\n",
      "Epoch 362/1000\n",
      "12/12 [==============================] - 4s 331ms/step - loss: 0.1323 - sparse_categorical_crossentropy: 0.0530 - sparse_categorical_accuracy: 0.9864 - scaled_adversarial_loss: 0.0793 - val_loss: 0.0861 - val_sparse_categorical_crossentropy: 0.0376 - val_sparse_categorical_accuracy: 0.9881 - val_scaled_adversarial_loss: 0.0485\n",
      "Epoch 363/1000\n",
      "12/12 [==============================] - 4s 329ms/step - loss: 0.1210 - sparse_categorical_crossentropy: 0.0487 - sparse_categorical_accuracy: 0.9827 - scaled_adversarial_loss: 0.0723 - val_loss: 0.0938 - val_sparse_categorical_crossentropy: 0.0402 - val_sparse_categorical_accuracy: 0.9860 - val_scaled_adversarial_loss: 0.0536\n",
      "Epoch 364/1000\n",
      "12/12 [==============================] - 4s 331ms/step - loss: 0.1304 - sparse_categorical_crossentropy: 0.0528 - sparse_categorical_accuracy: 0.9823 - scaled_adversarial_loss: 0.0776 - val_loss: 0.0839 - val_sparse_categorical_crossentropy: 0.0356 - val_sparse_categorical_accuracy: 0.9888 - val_scaled_adversarial_loss: 0.0483\n",
      "Epoch 365/1000\n",
      "12/12 [==============================] - 4s 329ms/step - loss: 0.1244 - sparse_categorical_crossentropy: 0.0465 - sparse_categorical_accuracy: 0.9857 - scaled_adversarial_loss: 0.0779 - val_loss: 0.0951 - val_sparse_categorical_crossentropy: 0.0417 - val_sparse_categorical_accuracy: 0.9888 - val_scaled_adversarial_loss: 0.0534\n",
      "Epoch 366/1000\n",
      "12/12 [==============================] - 4s 331ms/step - loss: 0.1278 - sparse_categorical_crossentropy: 0.0527 - sparse_categorical_accuracy: 0.9820 - scaled_adversarial_loss: 0.0751 - val_loss: 0.0815 - val_sparse_categorical_crossentropy: 0.0340 - val_sparse_categorical_accuracy: 0.9895 - val_scaled_adversarial_loss: 0.0475\n",
      "Epoch 367/1000\n",
      "12/12 [==============================] - 4s 329ms/step - loss: 0.1229 - sparse_categorical_crossentropy: 0.0458 - sparse_categorical_accuracy: 0.9829 - scaled_adversarial_loss: 0.0771 - val_loss: 0.0862 - val_sparse_categorical_crossentropy: 0.0346 - val_sparse_categorical_accuracy: 0.9881 - val_scaled_adversarial_loss: 0.0516\n",
      "Epoch 368/1000\n",
      "12/12 [==============================] - 4s 330ms/step - loss: 0.1161 - sparse_categorical_crossentropy: 0.0430 - sparse_categorical_accuracy: 0.9839 - scaled_adversarial_loss: 0.0731 - val_loss: 0.0827 - val_sparse_categorical_crossentropy: 0.0393 - val_sparse_categorical_accuracy: 0.9874 - val_scaled_adversarial_loss: 0.0434\n",
      "Epoch 369/1000\n",
      "12/12 [==============================] - 4s 372ms/step - loss: 0.1183 - sparse_categorical_crossentropy: 0.0509 - sparse_categorical_accuracy: 0.9806 - scaled_adversarial_loss: 0.0674 - val_loss: 0.0946 - val_sparse_categorical_crossentropy: 0.0447 - val_sparse_categorical_accuracy: 0.9881 - val_scaled_adversarial_loss: 0.0499\n",
      "Epoch 370/1000\n",
      "12/12 [==============================] - 4s 370ms/step - loss: 0.1366 - sparse_categorical_crossentropy: 0.0554 - sparse_categorical_accuracy: 0.9811 - scaled_adversarial_loss: 0.0812 - val_loss: 0.0938 - val_sparse_categorical_crossentropy: 0.0361 - val_sparse_categorical_accuracy: 0.9888 - val_scaled_adversarial_loss: 0.0576\n",
      "Epoch 371/1000\n",
      "12/12 [==============================] - 4s 363ms/step - loss: 0.1297 - sparse_categorical_crossentropy: 0.0479 - sparse_categorical_accuracy: 0.9846 - scaled_adversarial_loss: 0.0818 - val_loss: 0.0971 - val_sparse_categorical_crossentropy: 0.0397 - val_sparse_categorical_accuracy: 0.9881 - val_scaled_adversarial_loss: 0.0574\n",
      "Epoch 372/1000\n",
      "12/12 [==============================] - 4s 354ms/step - loss: 0.1239 - sparse_categorical_crossentropy: 0.0475 - sparse_categorical_accuracy: 0.9836 - scaled_adversarial_loss: 0.0764 - val_loss: 0.0854 - val_sparse_categorical_crossentropy: 0.0368 - val_sparse_categorical_accuracy: 0.9881 - val_scaled_adversarial_loss: 0.0486\n",
      "Epoch 373/1000\n",
      "12/12 [==============================] - 4s 345ms/step - loss: 0.1224 - sparse_categorical_crossentropy: 0.0477 - sparse_categorical_accuracy: 0.9830 - scaled_adversarial_loss: 0.0747 - val_loss: 0.0867 - val_sparse_categorical_crossentropy: 0.0354 - val_sparse_categorical_accuracy: 0.9881 - val_scaled_adversarial_loss: 0.0513\n",
      "Epoch 374/1000\n",
      "12/12 [==============================] - 4s 374ms/step - loss: 0.1234 - sparse_categorical_crossentropy: 0.0452 - sparse_categorical_accuracy: 0.9832 - scaled_adversarial_loss: 0.0782 - val_loss: 0.0966 - val_sparse_categorical_crossentropy: 0.0424 - val_sparse_categorical_accuracy: 0.9860 - val_scaled_adversarial_loss: 0.0542\n",
      "Epoch 375/1000\n",
      "12/12 [==============================] - 4s 369ms/step - loss: 0.1208 - sparse_categorical_crossentropy: 0.0500 - sparse_categorical_accuracy: 0.9829 - scaled_adversarial_loss: 0.0708 - val_loss: 0.1067 - val_sparse_categorical_crossentropy: 0.0499 - val_sparse_categorical_accuracy: 0.9839 - val_scaled_adversarial_loss: 0.0568\n",
      "Epoch 376/1000\n",
      "12/12 [==============================] - 5s 394ms/step - loss: 0.1281 - sparse_categorical_crossentropy: 0.0551 - sparse_categorical_accuracy: 0.9816 - scaled_adversarial_loss: 0.0730 - val_loss: 0.0890 - val_sparse_categorical_crossentropy: 0.0438 - val_sparse_categorical_accuracy: 0.9839 - val_scaled_adversarial_loss: 0.0451\n",
      "Epoch 377/1000\n",
      "12/12 [==============================] - 4s 368ms/step - loss: 0.1135 - sparse_categorical_crossentropy: 0.0420 - sparse_categorical_accuracy: 0.9844 - scaled_adversarial_loss: 0.0715 - val_loss: 0.0845 - val_sparse_categorical_crossentropy: 0.0354 - val_sparse_categorical_accuracy: 0.9902 - val_scaled_adversarial_loss: 0.0492\n",
      "Epoch 378/1000\n",
      "12/12 [==============================] - 4s 365ms/step - loss: 0.1307 - sparse_categorical_crossentropy: 0.0506 - sparse_categorical_accuracy: 0.9815 - scaled_adversarial_loss: 0.0802 - val_loss: 0.0910 - val_sparse_categorical_crossentropy: 0.0361 - val_sparse_categorical_accuracy: 0.9881 - val_scaled_adversarial_loss: 0.0550\n",
      "Epoch 379/1000\n",
      "12/12 [==============================] - 4s 351ms/step - loss: 0.1275 - sparse_categorical_crossentropy: 0.0490 - sparse_categorical_accuracy: 0.9818 - scaled_adversarial_loss: 0.0785 - val_loss: 0.0796 - val_sparse_categorical_crossentropy: 0.0367 - val_sparse_categorical_accuracy: 0.9881 - val_scaled_adversarial_loss: 0.0429\n",
      "Epoch 380/1000\n",
      "12/12 [==============================] - 4s 348ms/step - loss: 0.1229 - sparse_categorical_crossentropy: 0.0494 - sparse_categorical_accuracy: 0.9809 - scaled_adversarial_loss: 0.0735 - val_loss: 0.0839 - val_sparse_categorical_crossentropy: 0.0338 - val_sparse_categorical_accuracy: 0.9895 - val_scaled_adversarial_loss: 0.0501\n",
      "Epoch 381/1000\n",
      "12/12 [==============================] - 4s 361ms/step - loss: 0.1120 - sparse_categorical_crossentropy: 0.0417 - sparse_categorical_accuracy: 0.9846 - scaled_adversarial_loss: 0.0703 - val_loss: 0.0776 - val_sparse_categorical_crossentropy: 0.0364 - val_sparse_categorical_accuracy: 0.9902 - val_scaled_adversarial_loss: 0.0412\n",
      "Epoch 382/1000\n",
      "12/12 [==============================] - 4s 347ms/step - loss: 0.1135 - sparse_categorical_crossentropy: 0.0447 - sparse_categorical_accuracy: 0.9851 - scaled_adversarial_loss: 0.0688 - val_loss: 0.0768 - val_sparse_categorical_crossentropy: 0.0357 - val_sparse_categorical_accuracy: 0.9895 - val_scaled_adversarial_loss: 0.0411\n",
      "Epoch 383/1000\n",
      "12/12 [==============================] - 4s 342ms/step - loss: 0.1152 - sparse_categorical_crossentropy: 0.0424 - sparse_categorical_accuracy: 0.9862 - scaled_adversarial_loss: 0.0727 - val_loss: 0.0784 - val_sparse_categorical_crossentropy: 0.0335 - val_sparse_categorical_accuracy: 0.9867 - val_scaled_adversarial_loss: 0.0449\n",
      "Epoch 384/1000\n",
      "12/12 [==============================] - 4s 346ms/step - loss: 0.1141 - sparse_categorical_crossentropy: 0.0430 - sparse_categorical_accuracy: 0.9857 - scaled_adversarial_loss: 0.0711 - val_loss: 0.0795 - val_sparse_categorical_crossentropy: 0.0343 - val_sparse_categorical_accuracy: 0.9888 - val_scaled_adversarial_loss: 0.0452\n",
      "Epoch 385/1000\n",
      "12/12 [==============================] - 4s 351ms/step - loss: 0.1194 - sparse_categorical_crossentropy: 0.0482 - sparse_categorical_accuracy: 0.9830 - scaled_adversarial_loss: 0.0712 - val_loss: 0.0883 - val_sparse_categorical_crossentropy: 0.0365 - val_sparse_categorical_accuracy: 0.9895 - val_scaled_adversarial_loss: 0.0518\n",
      "Epoch 386/1000\n",
      "12/12 [==============================] - 4s 342ms/step - loss: 0.1276 - sparse_categorical_crossentropy: 0.0500 - sparse_categorical_accuracy: 0.9846 - scaled_adversarial_loss: 0.0776 - val_loss: 0.0856 - val_sparse_categorical_crossentropy: 0.0398 - val_sparse_categorical_accuracy: 0.9881 - val_scaled_adversarial_loss: 0.0457\n",
      "Epoch 387/1000\n",
      "12/12 [==============================] - 5s 380ms/step - loss: 0.1209 - sparse_categorical_crossentropy: 0.0474 - sparse_categorical_accuracy: 0.9808 - scaled_adversarial_loss: 0.0735 - val_loss: 0.0885 - val_sparse_categorical_crossentropy: 0.0392 - val_sparse_categorical_accuracy: 0.9874 - val_scaled_adversarial_loss: 0.0493\n",
      "Epoch 388/1000\n",
      "12/12 [==============================] - 5s 381ms/step - loss: 0.1259 - sparse_categorical_crossentropy: 0.0457 - sparse_categorical_accuracy: 0.9876 - scaled_adversarial_loss: 0.0802 - val_loss: 0.0866 - val_sparse_categorical_crossentropy: 0.0391 - val_sparse_categorical_accuracy: 0.9881 - val_scaled_adversarial_loss: 0.0475\n",
      "Epoch 389/1000\n",
      "12/12 [==============================] - 4s 361ms/step - loss: 0.1230 - sparse_categorical_crossentropy: 0.0441 - sparse_categorical_accuracy: 0.9823 - scaled_adversarial_loss: 0.0790 - val_loss: 0.0884 - val_sparse_categorical_crossentropy: 0.0379 - val_sparse_categorical_accuracy: 0.9867 - val_scaled_adversarial_loss: 0.0505\n",
      "Epoch 390/1000\n",
      "12/12 [==============================] - 4s 360ms/step - loss: 0.1164 - sparse_categorical_crossentropy: 0.0458 - sparse_categorical_accuracy: 0.9839 - scaled_adversarial_loss: 0.0706 - val_loss: 0.0863 - val_sparse_categorical_crossentropy: 0.0347 - val_sparse_categorical_accuracy: 0.9895 - val_scaled_adversarial_loss: 0.0516\n",
      "Epoch 391/1000\n",
      "12/12 [==============================] - 4s 337ms/step - loss: 0.1295 - sparse_categorical_crossentropy: 0.0447 - sparse_categorical_accuracy: 0.9848 - scaled_adversarial_loss: 0.0849 - val_loss: 0.0856 - val_sparse_categorical_crossentropy: 0.0369 - val_sparse_categorical_accuracy: 0.9888 - val_scaled_adversarial_loss: 0.0487\n",
      "Epoch 392/1000\n",
      "12/12 [==============================] - 4s 346ms/step - loss: 0.1136 - sparse_categorical_crossentropy: 0.0414 - sparse_categorical_accuracy: 0.9860 - scaled_adversarial_loss: 0.0722 - val_loss: 0.0831 - val_sparse_categorical_crossentropy: 0.0371 - val_sparse_categorical_accuracy: 0.9881 - val_scaled_adversarial_loss: 0.0461\n",
      "Epoch 393/1000\n",
      "12/12 [==============================] - 4s 352ms/step - loss: 0.1188 - sparse_categorical_crossentropy: 0.0437 - sparse_categorical_accuracy: 0.9839 - scaled_adversarial_loss: 0.0751 - val_loss: 0.0800 - val_sparse_categorical_crossentropy: 0.0353 - val_sparse_categorical_accuracy: 0.9909 - val_scaled_adversarial_loss: 0.0446\n",
      "Epoch 394/1000\n",
      "12/12 [==============================] - 4s 372ms/step - loss: 0.1233 - sparse_categorical_crossentropy: 0.0480 - sparse_categorical_accuracy: 0.9857 - scaled_adversarial_loss: 0.0752 - val_loss: 0.0871 - val_sparse_categorical_crossentropy: 0.0383 - val_sparse_categorical_accuracy: 0.9881 - val_scaled_adversarial_loss: 0.0489\n",
      "Epoch 395/1000\n",
      "12/12 [==============================] - 4s 368ms/step - loss: 0.1269 - sparse_categorical_crossentropy: 0.0477 - sparse_categorical_accuracy: 0.9848 - scaled_adversarial_loss: 0.0792 - val_loss: 0.0958 - val_sparse_categorical_crossentropy: 0.0500 - val_sparse_categorical_accuracy: 0.9874 - val_scaled_adversarial_loss: 0.0458\n",
      "Epoch 396/1000\n",
      "12/12 [==============================] - 4s 368ms/step - loss: 0.1170 - sparse_categorical_crossentropy: 0.0426 - sparse_categorical_accuracy: 0.9869 - scaled_adversarial_loss: 0.0744 - val_loss: 0.0854 - val_sparse_categorical_crossentropy: 0.0432 - val_sparse_categorical_accuracy: 0.9867 - val_scaled_adversarial_loss: 0.0422\n",
      "Epoch 397/1000\n",
      "12/12 [==============================] - 4s 375ms/step - loss: 0.1208 - sparse_categorical_crossentropy: 0.0427 - sparse_categorical_accuracy: 0.9841 - scaled_adversarial_loss: 0.0782 - val_loss: 0.0814 - val_sparse_categorical_crossentropy: 0.0389 - val_sparse_categorical_accuracy: 0.9881 - val_scaled_adversarial_loss: 0.0425\n",
      "Epoch 398/1000\n",
      "12/12 [==============================] - 4s 377ms/step - loss: 0.1273 - sparse_categorical_crossentropy: 0.0498 - sparse_categorical_accuracy: 0.9811 - scaled_adversarial_loss: 0.0774 - val_loss: 0.0861 - val_sparse_categorical_crossentropy: 0.0351 - val_sparse_categorical_accuracy: 0.9895 - val_scaled_adversarial_loss: 0.0510\n",
      "Epoch 399/1000\n",
      "12/12 [==============================] - 5s 405ms/step - loss: 0.1271 - sparse_categorical_crossentropy: 0.0496 - sparse_categorical_accuracy: 0.9844 - scaled_adversarial_loss: 0.0775 - val_loss: 0.0807 - val_sparse_categorical_crossentropy: 0.0378 - val_sparse_categorical_accuracy: 0.9881 - val_scaled_adversarial_loss: 0.0429\n",
      "Epoch 400/1000\n",
      "12/12 [==============================] - 4s 371ms/step - loss: 0.1219 - sparse_categorical_crossentropy: 0.0451 - sparse_categorical_accuracy: 0.9834 - scaled_adversarial_loss: 0.0768 - val_loss: 0.0798 - val_sparse_categorical_crossentropy: 0.0332 - val_sparse_categorical_accuracy: 0.9916 - val_scaled_adversarial_loss: 0.0466\n",
      "Epoch 401/1000\n",
      "12/12 [==============================] - 5s 378ms/step - loss: 0.1186 - sparse_categorical_crossentropy: 0.0444 - sparse_categorical_accuracy: 0.9836 - scaled_adversarial_loss: 0.0742 - val_loss: 0.0764 - val_sparse_categorical_crossentropy: 0.0330 - val_sparse_categorical_accuracy: 0.9881 - val_scaled_adversarial_loss: 0.0434\n",
      "Epoch 402/1000\n",
      "12/12 [==============================] - 4s 353ms/step - loss: 0.1192 - sparse_categorical_crossentropy: 0.0419 - sparse_categorical_accuracy: 0.9855 - scaled_adversarial_loss: 0.0774 - val_loss: 0.0780 - val_sparse_categorical_crossentropy: 0.0356 - val_sparse_categorical_accuracy: 0.9895 - val_scaled_adversarial_loss: 0.0424\n",
      "Epoch 403/1000\n",
      "12/12 [==============================] - 4s 346ms/step - loss: 0.1178 - sparse_categorical_crossentropy: 0.0468 - sparse_categorical_accuracy: 0.9832 - scaled_adversarial_loss: 0.0710 - val_loss: 0.0793 - val_sparse_categorical_crossentropy: 0.0406 - val_sparse_categorical_accuracy: 0.9888 - val_scaled_adversarial_loss: 0.0387\n",
      "Epoch 404/1000\n",
      "12/12 [==============================] - 4s 346ms/step - loss: 0.1136 - sparse_categorical_crossentropy: 0.0391 - sparse_categorical_accuracy: 0.9874 - scaled_adversarial_loss: 0.0745 - val_loss: 0.0815 - val_sparse_categorical_crossentropy: 0.0419 - val_sparse_categorical_accuracy: 0.9902 - val_scaled_adversarial_loss: 0.0396\n",
      "Epoch 405/1000\n",
      "12/12 [==============================] - 4s 347ms/step - loss: 0.1181 - sparse_categorical_crossentropy: 0.0420 - sparse_categorical_accuracy: 0.9857 - scaled_adversarial_loss: 0.0762 - val_loss: 0.0846 - val_sparse_categorical_crossentropy: 0.0401 - val_sparse_categorical_accuracy: 0.9853 - val_scaled_adversarial_loss: 0.0446\n",
      "Epoch 406/1000\n",
      "12/12 [==============================] - 4s 338ms/step - loss: 0.1242 - sparse_categorical_crossentropy: 0.0466 - sparse_categorical_accuracy: 0.9825 - scaled_adversarial_loss: 0.0775 - val_loss: 0.0894 - val_sparse_categorical_crossentropy: 0.0365 - val_sparse_categorical_accuracy: 0.9853 - val_scaled_adversarial_loss: 0.0530\n",
      "Epoch 407/1000\n",
      "12/12 [==============================] - 4s 336ms/step - loss: 0.1189 - sparse_categorical_crossentropy: 0.0422 - sparse_categorical_accuracy: 0.9848 - scaled_adversarial_loss: 0.0767 - val_loss: 0.0836 - val_sparse_categorical_crossentropy: 0.0335 - val_sparse_categorical_accuracy: 0.9881 - val_scaled_adversarial_loss: 0.0501\n",
      "Epoch 408/1000\n",
      "12/12 [==============================] - 4s 338ms/step - loss: 0.1186 - sparse_categorical_crossentropy: 0.0401 - sparse_categorical_accuracy: 0.9865 - scaled_adversarial_loss: 0.0785 - val_loss: 0.0809 - val_sparse_categorical_crossentropy: 0.0343 - val_sparse_categorical_accuracy: 0.9916 - val_scaled_adversarial_loss: 0.0466\n",
      "Epoch 409/1000\n",
      "12/12 [==============================] - 4s 342ms/step - loss: 0.1173 - sparse_categorical_crossentropy: 0.0402 - sparse_categorical_accuracy: 0.9876 - scaled_adversarial_loss: 0.0771 - val_loss: 0.0794 - val_sparse_categorical_crossentropy: 0.0359 - val_sparse_categorical_accuracy: 0.9902 - val_scaled_adversarial_loss: 0.0435\n",
      "Epoch 410/1000\n",
      "12/12 [==============================] - 4s 346ms/step - loss: 0.1151 - sparse_categorical_crossentropy: 0.0419 - sparse_categorical_accuracy: 0.9850 - scaled_adversarial_loss: 0.0732 - val_loss: 0.0875 - val_sparse_categorical_crossentropy: 0.0374 - val_sparse_categorical_accuracy: 0.9902 - val_scaled_adversarial_loss: 0.0501\n",
      "Epoch 411/1000\n",
      "12/12 [==============================] - 4s 338ms/step - loss: 0.1116 - sparse_categorical_crossentropy: 0.0376 - sparse_categorical_accuracy: 0.9886 - scaled_adversarial_loss: 0.0741 - val_loss: 0.0878 - val_sparse_categorical_crossentropy: 0.0366 - val_sparse_categorical_accuracy: 0.9881 - val_scaled_adversarial_loss: 0.0511\n",
      "Epoch 412/1000\n",
      "12/12 [==============================] - 4s 337ms/step - loss: 0.1227 - sparse_categorical_crossentropy: 0.0456 - sparse_categorical_accuracy: 0.9844 - scaled_adversarial_loss: 0.0771 - val_loss: 0.0886 - val_sparse_categorical_crossentropy: 0.0450 - val_sparse_categorical_accuracy: 0.9867 - val_scaled_adversarial_loss: 0.0436\n",
      "Epoch 413/1000\n",
      "12/12 [==============================] - 4s 338ms/step - loss: 0.1163 - sparse_categorical_crossentropy: 0.0445 - sparse_categorical_accuracy: 0.9857 - scaled_adversarial_loss: 0.0717 - val_loss: 0.0835 - val_sparse_categorical_crossentropy: 0.0365 - val_sparse_categorical_accuracy: 0.9895 - val_scaled_adversarial_loss: 0.0470\n",
      "Epoch 414/1000\n",
      "12/12 [==============================] - 4s 337ms/step - loss: 0.1279 - sparse_categorical_crossentropy: 0.0502 - sparse_categorical_accuracy: 0.9850 - scaled_adversarial_loss: 0.0777 - val_loss: 0.0845 - val_sparse_categorical_crossentropy: 0.0369 - val_sparse_categorical_accuracy: 0.9888 - val_scaled_adversarial_loss: 0.0476\n",
      "Epoch 415/1000\n",
      "12/12 [==============================] - 4s 348ms/step - loss: 0.1314 - sparse_categorical_crossentropy: 0.0571 - sparse_categorical_accuracy: 0.9822 - scaled_adversarial_loss: 0.0743 - val_loss: 0.0926 - val_sparse_categorical_crossentropy: 0.0366 - val_sparse_categorical_accuracy: 0.9867 - val_scaled_adversarial_loss: 0.0560\n",
      "Epoch 416/1000\n",
      "12/12 [==============================] - 4s 335ms/step - loss: 0.1408 - sparse_categorical_crossentropy: 0.0568 - sparse_categorical_accuracy: 0.9830 - scaled_adversarial_loss: 0.0839 - val_loss: 0.0959 - val_sparse_categorical_crossentropy: 0.0410 - val_sparse_categorical_accuracy: 0.9839 - val_scaled_adversarial_loss: 0.0549\n",
      "Epoch 417/1000\n",
      "12/12 [==============================] - 4s 344ms/step - loss: 0.1398 - sparse_categorical_crossentropy: 0.0615 - sparse_categorical_accuracy: 0.9811 - scaled_adversarial_loss: 0.0783 - val_loss: 0.1048 - val_sparse_categorical_crossentropy: 0.0494 - val_sparse_categorical_accuracy: 0.9839 - val_scaled_adversarial_loss: 0.0553\n",
      "Epoch 418/1000\n",
      "12/12 [==============================] - 4s 341ms/step - loss: 0.1264 - sparse_categorical_crossentropy: 0.0474 - sparse_categorical_accuracy: 0.9822 - scaled_adversarial_loss: 0.0790 - val_loss: 0.0897 - val_sparse_categorical_crossentropy: 0.0347 - val_sparse_categorical_accuracy: 0.9881 - val_scaled_adversarial_loss: 0.0550\n",
      "Epoch 419/1000\n",
      "12/12 [==============================] - 4s 341ms/step - loss: 0.1173 - sparse_categorical_crossentropy: 0.0388 - sparse_categorical_accuracy: 0.9850 - scaled_adversarial_loss: 0.0786 - val_loss: 0.0771 - val_sparse_categorical_crossentropy: 0.0323 - val_sparse_categorical_accuracy: 0.9909 - val_scaled_adversarial_loss: 0.0448\n",
      "Epoch 420/1000\n",
      "12/12 [==============================] - 4s 340ms/step - loss: 0.1134 - sparse_categorical_crossentropy: 0.0392 - sparse_categorical_accuracy: 0.9874 - scaled_adversarial_loss: 0.0742 - val_loss: 0.0931 - val_sparse_categorical_crossentropy: 0.0381 - val_sparse_categorical_accuracy: 0.9916 - val_scaled_adversarial_loss: 0.0551\n",
      "Epoch 421/1000\n",
      "12/12 [==============================] - 4s 342ms/step - loss: 0.1198 - sparse_categorical_crossentropy: 0.0390 - sparse_categorical_accuracy: 0.9878 - scaled_adversarial_loss: 0.0808 - val_loss: 0.0901 - val_sparse_categorical_crossentropy: 0.0410 - val_sparse_categorical_accuracy: 0.9881 - val_scaled_adversarial_loss: 0.0492\n",
      "Epoch 422/1000\n",
      "12/12 [==============================] - 4s 343ms/step - loss: 0.1159 - sparse_categorical_crossentropy: 0.0379 - sparse_categorical_accuracy: 0.9869 - scaled_adversarial_loss: 0.0780 - val_loss: 0.0909 - val_sparse_categorical_crossentropy: 0.0391 - val_sparse_categorical_accuracy: 0.9909 - val_scaled_adversarial_loss: 0.0517\n",
      "Epoch 423/1000\n",
      "12/12 [==============================] - 4s 341ms/step - loss: 0.1109 - sparse_categorical_crossentropy: 0.0378 - sparse_categorical_accuracy: 0.9878 - scaled_adversarial_loss: 0.0730 - val_loss: 0.0885 - val_sparse_categorical_crossentropy: 0.0333 - val_sparse_categorical_accuracy: 0.9888 - val_scaled_adversarial_loss: 0.0551\n",
      "Epoch 424/1000\n",
      "12/12 [==============================] - 4s 341ms/step - loss: 0.1174 - sparse_categorical_crossentropy: 0.0435 - sparse_categorical_accuracy: 0.9827 - scaled_adversarial_loss: 0.0739 - val_loss: 0.0749 - val_sparse_categorical_crossentropy: 0.0350 - val_sparse_categorical_accuracy: 0.9888 - val_scaled_adversarial_loss: 0.0399\n",
      "Epoch 425/1000\n",
      "12/12 [==============================] - 4s 342ms/step - loss: 0.1190 - sparse_categorical_crossentropy: 0.0441 - sparse_categorical_accuracy: 0.9858 - scaled_adversarial_loss: 0.0750 - val_loss: 0.1046 - val_sparse_categorical_crossentropy: 0.0473 - val_sparse_categorical_accuracy: 0.9846 - val_scaled_adversarial_loss: 0.0573\n",
      "Epoch 426/1000\n",
      "12/12 [==============================] - 4s 344ms/step - loss: 0.1378 - sparse_categorical_crossentropy: 0.0552 - sparse_categorical_accuracy: 0.9802 - scaled_adversarial_loss: 0.0826 - val_loss: 0.0963 - val_sparse_categorical_crossentropy: 0.0358 - val_sparse_categorical_accuracy: 0.9881 - val_scaled_adversarial_loss: 0.0606\n",
      "Epoch 427/1000\n",
      "12/12 [==============================] - 4s 342ms/step - loss: 0.1292 - sparse_categorical_crossentropy: 0.0455 - sparse_categorical_accuracy: 0.9825 - scaled_adversarial_loss: 0.0837 - val_loss: 0.0842 - val_sparse_categorical_crossentropy: 0.0329 - val_sparse_categorical_accuracy: 0.9895 - val_scaled_adversarial_loss: 0.0512\n",
      "Epoch 428/1000\n",
      "12/12 [==============================] - 4s 340ms/step - loss: 0.1171 - sparse_categorical_crossentropy: 0.0388 - sparse_categorical_accuracy: 0.9860 - scaled_adversarial_loss: 0.0783 - val_loss: 0.0796 - val_sparse_categorical_crossentropy: 0.0322 - val_sparse_categorical_accuracy: 0.9902 - val_scaled_adversarial_loss: 0.0475\n",
      "Epoch 429/1000\n",
      "12/12 [==============================] - 4s 343ms/step - loss: 0.1176 - sparse_categorical_crossentropy: 0.0387 - sparse_categorical_accuracy: 0.9864 - scaled_adversarial_loss: 0.0789 - val_loss: 0.0778 - val_sparse_categorical_crossentropy: 0.0315 - val_sparse_categorical_accuracy: 0.9902 - val_scaled_adversarial_loss: 0.0463\n",
      "Epoch 430/1000\n",
      "12/12 [==============================] - 4s 353ms/step - loss: 0.1137 - sparse_categorical_crossentropy: 0.0381 - sparse_categorical_accuracy: 0.9867 - scaled_adversarial_loss: 0.0756 - val_loss: 0.0751 - val_sparse_categorical_crossentropy: 0.0325 - val_sparse_categorical_accuracy: 0.9902 - val_scaled_adversarial_loss: 0.0425\n",
      "Epoch 431/1000\n",
      "12/12 [==============================] - 5s 397ms/step - loss: 0.1153 - sparse_categorical_crossentropy: 0.0372 - sparse_categorical_accuracy: 0.9874 - scaled_adversarial_loss: 0.0781 - val_loss: 0.0795 - val_sparse_categorical_crossentropy: 0.0315 - val_sparse_categorical_accuracy: 0.9895 - val_scaled_adversarial_loss: 0.0480\n",
      "Epoch 432/1000\n",
      "12/12 [==============================] - 5s 390ms/step - loss: 0.1194 - sparse_categorical_crossentropy: 0.0460 - sparse_categorical_accuracy: 0.9855 - scaled_adversarial_loss: 0.0734 - val_loss: 0.0853 - val_sparse_categorical_crossentropy: 0.0348 - val_sparse_categorical_accuracy: 0.9902 - val_scaled_adversarial_loss: 0.0505\n",
      "Epoch 433/1000\n",
      "12/12 [==============================] - 4s 365ms/step - loss: 0.1306 - sparse_categorical_crossentropy: 0.0542 - sparse_categorical_accuracy: 0.9829 - scaled_adversarial_loss: 0.0764 - val_loss: 0.1017 - val_sparse_categorical_crossentropy: 0.0391 - val_sparse_categorical_accuracy: 0.9895 - val_scaled_adversarial_loss: 0.0626\n",
      "Epoch 434/1000\n",
      "12/12 [==============================] - 4s 374ms/step - loss: 0.1237 - sparse_categorical_crossentropy: 0.0476 - sparse_categorical_accuracy: 0.9841 - scaled_adversarial_loss: 0.0761 - val_loss: 0.0937 - val_sparse_categorical_crossentropy: 0.0357 - val_sparse_categorical_accuracy: 0.9902 - val_scaled_adversarial_loss: 0.0580\n",
      "Epoch 435/1000\n",
      "12/12 [==============================] - 4s 347ms/step - loss: 0.1246 - sparse_categorical_crossentropy: 0.0468 - sparse_categorical_accuracy: 0.9843 - scaled_adversarial_loss: 0.0778 - val_loss: 0.0823 - val_sparse_categorical_crossentropy: 0.0328 - val_sparse_categorical_accuracy: 0.9895 - val_scaled_adversarial_loss: 0.0495\n",
      "Epoch 436/1000\n",
      "12/12 [==============================] - 4s 346ms/step - loss: 0.1297 - sparse_categorical_crossentropy: 0.0487 - sparse_categorical_accuracy: 0.9839 - scaled_adversarial_loss: 0.0810 - val_loss: 0.0853 - val_sparse_categorical_crossentropy: 0.0321 - val_sparse_categorical_accuracy: 0.9881 - val_scaled_adversarial_loss: 0.0532\n",
      "Epoch 437/1000\n",
      "12/12 [==============================] - 4s 350ms/step - loss: 0.1195 - sparse_categorical_crossentropy: 0.0437 - sparse_categorical_accuracy: 0.9871 - scaled_adversarial_loss: 0.0758 - val_loss: 0.0736 - val_sparse_categorical_crossentropy: 0.0320 - val_sparse_categorical_accuracy: 0.9923 - val_scaled_adversarial_loss: 0.0416\n",
      "Epoch 438/1000\n",
      "12/12 [==============================] - 4s 347ms/step - loss: 0.1225 - sparse_categorical_crossentropy: 0.0481 - sparse_categorical_accuracy: 0.9836 - scaled_adversarial_loss: 0.0744 - val_loss: 0.0744 - val_sparse_categorical_crossentropy: 0.0362 - val_sparse_categorical_accuracy: 0.9874 - val_scaled_adversarial_loss: 0.0382\n",
      "Epoch 439/1000\n",
      "12/12 [==============================] - 4s 347ms/step - loss: 0.1306 - sparse_categorical_crossentropy: 0.0527 - sparse_categorical_accuracy: 0.9808 - scaled_adversarial_loss: 0.0780 - val_loss: 0.1011 - val_sparse_categorical_crossentropy: 0.0380 - val_sparse_categorical_accuracy: 0.9895 - val_scaled_adversarial_loss: 0.0631\n",
      "Epoch 440/1000\n",
      "12/12 [==============================] - 4s 349ms/step - loss: 0.1181 - sparse_categorical_crossentropy: 0.0385 - sparse_categorical_accuracy: 0.9855 - scaled_adversarial_loss: 0.0796 - val_loss: 0.0770 - val_sparse_categorical_crossentropy: 0.0301 - val_sparse_categorical_accuracy: 0.9902 - val_scaled_adversarial_loss: 0.0469\n",
      "Epoch 441/1000\n",
      "12/12 [==============================] - 4s 359ms/step - loss: 0.1137 - sparse_categorical_crossentropy: 0.0371 - sparse_categorical_accuracy: 0.9886 - scaled_adversarial_loss: 0.0767 - val_loss: 0.0846 - val_sparse_categorical_crossentropy: 0.0338 - val_sparse_categorical_accuracy: 0.9874 - val_scaled_adversarial_loss: 0.0508\n",
      "Epoch 442/1000\n",
      "12/12 [==============================] - 4s 350ms/step - loss: 0.1122 - sparse_categorical_crossentropy: 0.0398 - sparse_categorical_accuracy: 0.9857 - scaled_adversarial_loss: 0.0724 - val_loss: 0.0929 - val_sparse_categorical_crossentropy: 0.0431 - val_sparse_categorical_accuracy: 0.9867 - val_scaled_adversarial_loss: 0.0498\n",
      "Epoch 443/1000\n",
      "12/12 [==============================] - 4s 349ms/step - loss: 0.1284 - sparse_categorical_crossentropy: 0.0498 - sparse_categorical_accuracy: 0.9860 - scaled_adversarial_loss: 0.0786 - val_loss: 0.0927 - val_sparse_categorical_crossentropy: 0.0428 - val_sparse_categorical_accuracy: 0.9881 - val_scaled_adversarial_loss: 0.0499\n",
      "Epoch 444/1000\n",
      "12/12 [==============================] - 4s 346ms/step - loss: 0.1226 - sparse_categorical_crossentropy: 0.0470 - sparse_categorical_accuracy: 0.9832 - scaled_adversarial_loss: 0.0756 - val_loss: 0.0813 - val_sparse_categorical_crossentropy: 0.0308 - val_sparse_categorical_accuracy: 0.9902 - val_scaled_adversarial_loss: 0.0505\n",
      "Epoch 445/1000\n",
      "12/12 [==============================] - 4s 348ms/step - loss: 0.1184 - sparse_categorical_crossentropy: 0.0410 - sparse_categorical_accuracy: 0.9865 - scaled_adversarial_loss: 0.0774 - val_loss: 0.0974 - val_sparse_categorical_crossentropy: 0.0356 - val_sparse_categorical_accuracy: 0.9881 - val_scaled_adversarial_loss: 0.0619\n",
      "Epoch 446/1000\n",
      "12/12 [==============================] - 4s 328ms/step - loss: 0.1293 - sparse_categorical_crossentropy: 0.0486 - sparse_categorical_accuracy: 0.9829 - scaled_adversarial_loss: 0.0807 - val_loss: 0.0784 - val_sparse_categorical_crossentropy: 0.0325 - val_sparse_categorical_accuracy: 0.9902 - val_scaled_adversarial_loss: 0.0459\n",
      "Epoch 447/1000\n",
      "12/12 [==============================] - 4s 364ms/step - loss: 0.1121 - sparse_categorical_crossentropy: 0.0391 - sparse_categorical_accuracy: 0.9857 - scaled_adversarial_loss: 0.0730 - val_loss: 0.0915 - val_sparse_categorical_crossentropy: 0.0449 - val_sparse_categorical_accuracy: 0.9895 - val_scaled_adversarial_loss: 0.0466\n",
      "Epoch 448/1000\n",
      "12/12 [==============================] - 4s 360ms/step - loss: 0.1280 - sparse_categorical_crossentropy: 0.0423 - sparse_categorical_accuracy: 0.9850 - scaled_adversarial_loss: 0.0857 - val_loss: 0.0793 - val_sparse_categorical_crossentropy: 0.0291 - val_sparse_categorical_accuracy: 0.9916 - val_scaled_adversarial_loss: 0.0502\n",
      "Epoch 449/1000\n",
      "12/12 [==============================] - 5s 401ms/step - loss: 0.1196 - sparse_categorical_crossentropy: 0.0451 - sparse_categorical_accuracy: 0.9853 - scaled_adversarial_loss: 0.0746 - val_loss: 0.0843 - val_sparse_categorical_crossentropy: 0.0386 - val_sparse_categorical_accuracy: 0.9895 - val_scaled_adversarial_loss: 0.0457\n",
      "Epoch 450/1000\n",
      "12/12 [==============================] - 4s 366ms/step - loss: 0.1178 - sparse_categorical_crossentropy: 0.0417 - sparse_categorical_accuracy: 0.9844 - scaled_adversarial_loss: 0.0761 - val_loss: 0.0790 - val_sparse_categorical_crossentropy: 0.0348 - val_sparse_categorical_accuracy: 0.9895 - val_scaled_adversarial_loss: 0.0443\n",
      "Epoch 451/1000\n",
      "12/12 [==============================] - 4s 346ms/step - loss: 0.1107 - sparse_categorical_crossentropy: 0.0419 - sparse_categorical_accuracy: 0.9865 - scaled_adversarial_loss: 0.0688 - val_loss: 0.0990 - val_sparse_categorical_crossentropy: 0.0466 - val_sparse_categorical_accuracy: 0.9888 - val_scaled_adversarial_loss: 0.0524\n",
      "Epoch 452/1000\n",
      "12/12 [==============================] - 4s 344ms/step - loss: 0.1284 - sparse_categorical_crossentropy: 0.0502 - sparse_categorical_accuracy: 0.9808 - scaled_adversarial_loss: 0.0782 - val_loss: 0.1551 - val_sparse_categorical_crossentropy: 0.0874 - val_sparse_categorical_accuracy: 0.9664 - val_scaled_adversarial_loss: 0.0677\n",
      "Epoch 453/1000\n",
      "12/12 [==============================] - 4s 361ms/step - loss: 0.1445 - sparse_categorical_crossentropy: 0.0629 - sparse_categorical_accuracy: 0.9778 - scaled_adversarial_loss: 0.0816 - val_loss: 0.1062 - val_sparse_categorical_crossentropy: 0.0474 - val_sparse_categorical_accuracy: 0.9874 - val_scaled_adversarial_loss: 0.0587\n",
      "Epoch 454/1000\n",
      "12/12 [==============================] - 4s 374ms/step - loss: 0.1345 - sparse_categorical_crossentropy: 0.0565 - sparse_categorical_accuracy: 0.9799 - scaled_adversarial_loss: 0.0780 - val_loss: 0.0682 - val_sparse_categorical_crossentropy: 0.0293 - val_sparse_categorical_accuracy: 0.9874 - val_scaled_adversarial_loss: 0.0389\n",
      "Epoch 455/1000\n",
      "12/12 [==============================] - 4s 358ms/step - loss: 0.1173 - sparse_categorical_crossentropy: 0.0455 - sparse_categorical_accuracy: 0.9846 - scaled_adversarial_loss: 0.0718 - val_loss: 0.0834 - val_sparse_categorical_crossentropy: 0.0407 - val_sparse_categorical_accuracy: 0.9902 - val_scaled_adversarial_loss: 0.0427\n",
      "Epoch 456/1000\n",
      "12/12 [==============================] - 4s 365ms/step - loss: 0.1181 - sparse_categorical_crossentropy: 0.0366 - sparse_categorical_accuracy: 0.9881 - scaled_adversarial_loss: 0.0815 - val_loss: 0.0808 - val_sparse_categorical_crossentropy: 0.0348 - val_sparse_categorical_accuracy: 0.9909 - val_scaled_adversarial_loss: 0.0459\n",
      "Epoch 457/1000\n",
      "12/12 [==============================] - 4s 353ms/step - loss: 0.1298 - sparse_categorical_crossentropy: 0.0481 - sparse_categorical_accuracy: 0.9829 - scaled_adversarial_loss: 0.0816 - val_loss: 0.0855 - val_sparse_categorical_crossentropy: 0.0351 - val_sparse_categorical_accuracy: 0.9909 - val_scaled_adversarial_loss: 0.0504\n",
      "Epoch 458/1000\n",
      "12/12 [==============================] - 4s 348ms/step - loss: 0.1189 - sparse_categorical_crossentropy: 0.0464 - sparse_categorical_accuracy: 0.9848 - scaled_adversarial_loss: 0.0725 - val_loss: 0.0926 - val_sparse_categorical_crossentropy: 0.0388 - val_sparse_categorical_accuracy: 0.9895 - val_scaled_adversarial_loss: 0.0538\n",
      "Epoch 459/1000\n",
      "12/12 [==============================] - 4s 337ms/step - loss: 0.1184 - sparse_categorical_crossentropy: 0.0453 - sparse_categorical_accuracy: 0.9829 - scaled_adversarial_loss: 0.0731 - val_loss: 0.0971 - val_sparse_categorical_crossentropy: 0.0398 - val_sparse_categorical_accuracy: 0.9860 - val_scaled_adversarial_loss: 0.0573\n",
      "Epoch 460/1000\n",
      "12/12 [==============================] - 4s 348ms/step - loss: 0.1337 - sparse_categorical_crossentropy: 0.0500 - sparse_categorical_accuracy: 0.9804 - scaled_adversarial_loss: 0.0838 - val_loss: 0.0838 - val_sparse_categorical_crossentropy: 0.0339 - val_sparse_categorical_accuracy: 0.9909 - val_scaled_adversarial_loss: 0.0498\n",
      "Epoch 461/1000\n",
      "12/12 [==============================] - 4s 342ms/step - loss: 0.1231 - sparse_categorical_crossentropy: 0.0477 - sparse_categorical_accuracy: 0.9818 - scaled_adversarial_loss: 0.0755 - val_loss: 0.0823 - val_sparse_categorical_crossentropy: 0.0320 - val_sparse_categorical_accuracy: 0.9916 - val_scaled_adversarial_loss: 0.0502\n",
      "Epoch 462/1000\n",
      "12/12 [==============================] - 4s 350ms/step - loss: 0.1168 - sparse_categorical_crossentropy: 0.0415 - sparse_categorical_accuracy: 0.9858 - scaled_adversarial_loss: 0.0752 - val_loss: 0.0772 - val_sparse_categorical_crossentropy: 0.0326 - val_sparse_categorical_accuracy: 0.9895 - val_scaled_adversarial_loss: 0.0446\n",
      "Epoch 463/1000\n",
      "12/12 [==============================] - 4s 354ms/step - loss: 0.1181 - sparse_categorical_crossentropy: 0.0387 - sparse_categorical_accuracy: 0.9867 - scaled_adversarial_loss: 0.0793 - val_loss: 0.0744 - val_sparse_categorical_crossentropy: 0.0268 - val_sparse_categorical_accuracy: 0.9937 - val_scaled_adversarial_loss: 0.0477\n",
      "Epoch 464/1000\n",
      "12/12 [==============================] - 4s 336ms/step - loss: 0.1160 - sparse_categorical_crossentropy: 0.0403 - sparse_categorical_accuracy: 0.9850 - scaled_adversarial_loss: 0.0757 - val_loss: 0.0729 - val_sparse_categorical_crossentropy: 0.0316 - val_sparse_categorical_accuracy: 0.9902 - val_scaled_adversarial_loss: 0.0413\n",
      "Epoch 465/1000\n",
      "12/12 [==============================] - 4s 372ms/step - loss: 0.1142 - sparse_categorical_crossentropy: 0.0359 - sparse_categorical_accuracy: 0.9879 - scaled_adversarial_loss: 0.0783 - val_loss: 0.0850 - val_sparse_categorical_crossentropy: 0.0324 - val_sparse_categorical_accuracy: 0.9874 - val_scaled_adversarial_loss: 0.0525\n",
      "Epoch 466/1000\n",
      "12/12 [==============================] - 5s 400ms/step - loss: 0.1204 - sparse_categorical_crossentropy: 0.0418 - sparse_categorical_accuracy: 0.9867 - scaled_adversarial_loss: 0.0785 - val_loss: 0.0801 - val_sparse_categorical_crossentropy: 0.0329 - val_sparse_categorical_accuracy: 0.9881 - val_scaled_adversarial_loss: 0.0472\n",
      "Epoch 467/1000\n",
      "12/12 [==============================] - 5s 399ms/step - loss: 0.1257 - sparse_categorical_crossentropy: 0.0439 - sparse_categorical_accuracy: 0.9855 - scaled_adversarial_loss: 0.0818 - val_loss: 0.0982 - val_sparse_categorical_crossentropy: 0.0381 - val_sparse_categorical_accuracy: 0.9895 - val_scaled_adversarial_loss: 0.0601\n",
      "Epoch 468/1000\n",
      "12/12 [==============================] - 4s 375ms/step - loss: 0.1137 - sparse_categorical_crossentropy: 0.0394 - sparse_categorical_accuracy: 0.9857 - scaled_adversarial_loss: 0.0743 - val_loss: 0.0898 - val_sparse_categorical_crossentropy: 0.0469 - val_sparse_categorical_accuracy: 0.9860 - val_scaled_adversarial_loss: 0.0429\n",
      "Epoch 469/1000\n",
      "12/12 [==============================] - 5s 387ms/step - loss: 0.1111 - sparse_categorical_crossentropy: 0.0405 - sparse_categorical_accuracy: 0.9857 - scaled_adversarial_loss: 0.0706 - val_loss: 0.0756 - val_sparse_categorical_crossentropy: 0.0296 - val_sparse_categorical_accuracy: 0.9867 - val_scaled_adversarial_loss: 0.0461\n",
      "Epoch 470/1000\n",
      "12/12 [==============================] - 4s 370ms/step - loss: 0.1229 - sparse_categorical_crossentropy: 0.0456 - sparse_categorical_accuracy: 0.9841 - scaled_adversarial_loss: 0.0773 - val_loss: 0.0831 - val_sparse_categorical_crossentropy: 0.0339 - val_sparse_categorical_accuracy: 0.9881 - val_scaled_adversarial_loss: 0.0493\n",
      "Epoch 471/1000\n",
      "12/12 [==============================] - 5s 437ms/step - loss: 0.1135 - sparse_categorical_crossentropy: 0.0389 - sparse_categorical_accuracy: 0.9871 - scaled_adversarial_loss: 0.0746 - val_loss: 0.0755 - val_sparse_categorical_crossentropy: 0.0345 - val_sparse_categorical_accuracy: 0.9916 - val_scaled_adversarial_loss: 0.0410\n",
      "Epoch 472/1000\n",
      "12/12 [==============================] - 5s 430ms/step - loss: 0.1184 - sparse_categorical_crossentropy: 0.0388 - sparse_categorical_accuracy: 0.9862 - scaled_adversarial_loss: 0.0796 - val_loss: 0.0818 - val_sparse_categorical_crossentropy: 0.0362 - val_sparse_categorical_accuracy: 0.9881 - val_scaled_adversarial_loss: 0.0456\n",
      "Epoch 473/1000\n",
      "12/12 [==============================] - 5s 429ms/step - loss: 0.1151 - sparse_categorical_crossentropy: 0.0392 - sparse_categorical_accuracy: 0.9860 - scaled_adversarial_loss: 0.0759 - val_loss: 0.0796 - val_sparse_categorical_crossentropy: 0.0351 - val_sparse_categorical_accuracy: 0.9895 - val_scaled_adversarial_loss: 0.0445\n",
      "Epoch 474/1000\n",
      "12/12 [==============================] - 5s 396ms/step - loss: 0.1233 - sparse_categorical_crossentropy: 0.0472 - sparse_categorical_accuracy: 0.9837 - scaled_adversarial_loss: 0.0761 - val_loss: 0.0904 - val_sparse_categorical_crossentropy: 0.0352 - val_sparse_categorical_accuracy: 0.9895 - val_scaled_adversarial_loss: 0.0552\n",
      "Epoch 475/1000\n",
      "12/12 [==============================] - 5s 459ms/step - loss: 0.1317 - sparse_categorical_crossentropy: 0.0465 - sparse_categorical_accuracy: 0.9850 - scaled_adversarial_loss: 0.0852 - val_loss: 0.0914 - val_sparse_categorical_crossentropy: 0.0429 - val_sparse_categorical_accuracy: 0.9860 - val_scaled_adversarial_loss: 0.0486\n",
      "Epoch 476/1000\n",
      "12/12 [==============================] - 5s 397ms/step - loss: 0.1418 - sparse_categorical_crossentropy: 0.0564 - sparse_categorical_accuracy: 0.9834 - scaled_adversarial_loss: 0.0854 - val_loss: 0.0887 - val_sparse_categorical_crossentropy: 0.0406 - val_sparse_categorical_accuracy: 0.9846 - val_scaled_adversarial_loss: 0.0481\n",
      "Epoch 477/1000\n",
      "12/12 [==============================] - 5s 393ms/step - loss: 0.1273 - sparse_categorical_crossentropy: 0.0451 - sparse_categorical_accuracy: 0.9858 - scaled_adversarial_loss: 0.0822 - val_loss: 0.0812 - val_sparse_categorical_crossentropy: 0.0360 - val_sparse_categorical_accuracy: 0.9888 - val_scaled_adversarial_loss: 0.0452\n",
      "Epoch 478/1000\n",
      "12/12 [==============================] - 5s 420ms/step - loss: 0.1249 - sparse_categorical_crossentropy: 0.0506 - sparse_categorical_accuracy: 0.9860 - scaled_adversarial_loss: 0.0743 - val_loss: 0.0947 - val_sparse_categorical_crossentropy: 0.0347 - val_sparse_categorical_accuracy: 0.9902 - val_scaled_adversarial_loss: 0.0600\n",
      "Epoch 479/1000\n",
      "12/12 [==============================] - 5s 400ms/step - loss: 0.1304 - sparse_categorical_crossentropy: 0.0521 - sparse_categorical_accuracy: 0.9820 - scaled_adversarial_loss: 0.0783 - val_loss: 0.0814 - val_sparse_categorical_crossentropy: 0.0397 - val_sparse_categorical_accuracy: 0.9895 - val_scaled_adversarial_loss: 0.0417\n",
      "Epoch 480/1000\n",
      "12/12 [==============================] - 5s 416ms/step - loss: 0.1182 - sparse_categorical_crossentropy: 0.0461 - sparse_categorical_accuracy: 0.9822 - scaled_adversarial_loss: 0.0721 - val_loss: 0.0942 - val_sparse_categorical_crossentropy: 0.0462 - val_sparse_categorical_accuracy: 0.9874 - val_scaled_adversarial_loss: 0.0480\n",
      "Epoch 481/1000\n",
      "12/12 [==============================] - 5s 415ms/step - loss: 0.1230 - sparse_categorical_crossentropy: 0.0457 - sparse_categorical_accuracy: 0.9848 - scaled_adversarial_loss: 0.0773 - val_loss: 0.0899 - val_sparse_categorical_crossentropy: 0.0373 - val_sparse_categorical_accuracy: 0.9902 - val_scaled_adversarial_loss: 0.0526\n",
      "Epoch 482/1000\n",
      "12/12 [==============================] - 5s 383ms/step - loss: 0.1253 - sparse_categorical_crossentropy: 0.0463 - sparse_categorical_accuracy: 0.9843 - scaled_adversarial_loss: 0.0790 - val_loss: 0.1027 - val_sparse_categorical_crossentropy: 0.0468 - val_sparse_categorical_accuracy: 0.9888 - val_scaled_adversarial_loss: 0.0559\n",
      "Epoch 483/1000\n",
      "12/12 [==============================] - 4s 355ms/step - loss: 0.1283 - sparse_categorical_crossentropy: 0.0523 - sparse_categorical_accuracy: 0.9836 - scaled_adversarial_loss: 0.0760 - val_loss: 0.0878 - val_sparse_categorical_crossentropy: 0.0394 - val_sparse_categorical_accuracy: 0.9895 - val_scaled_adversarial_loss: 0.0484\n",
      "Epoch 484/1000\n",
      "12/12 [==============================] - 5s 387ms/step - loss: 0.1338 - sparse_categorical_crossentropy: 0.0533 - sparse_categorical_accuracy: 0.9846 - scaled_adversarial_loss: 0.0805 - val_loss: 0.0885 - val_sparse_categorical_crossentropy: 0.0377 - val_sparse_categorical_accuracy: 0.9902 - val_scaled_adversarial_loss: 0.0509\n",
      "Epoch 485/1000\n",
      "12/12 [==============================] - 4s 363ms/step - loss: 0.1210 - sparse_categorical_crossentropy: 0.0462 - sparse_categorical_accuracy: 0.9844 - scaled_adversarial_loss: 0.0747 - val_loss: 0.0818 - val_sparse_categorical_crossentropy: 0.0371 - val_sparse_categorical_accuracy: 0.9895 - val_scaled_adversarial_loss: 0.0447\n",
      "Epoch 486/1000\n",
      "12/12 [==============================] - 4s 367ms/step - loss: 0.1117 - sparse_categorical_crossentropy: 0.0388 - sparse_categorical_accuracy: 0.9858 - scaled_adversarial_loss: 0.0729 - val_loss: 0.0789 - val_sparse_categorical_crossentropy: 0.0347 - val_sparse_categorical_accuracy: 0.9860 - val_scaled_adversarial_loss: 0.0442\n",
      "Epoch 487/1000\n",
      "12/12 [==============================] - 4s 363ms/step - loss: 0.1198 - sparse_categorical_crossentropy: 0.0384 - sparse_categorical_accuracy: 0.9855 - scaled_adversarial_loss: 0.0814 - val_loss: 0.0804 - val_sparse_categorical_crossentropy: 0.0310 - val_sparse_categorical_accuracy: 0.9902 - val_scaled_adversarial_loss: 0.0494\n",
      "Epoch 488/1000\n",
      "12/12 [==============================] - 5s 382ms/step - loss: 0.1124 - sparse_categorical_crossentropy: 0.0343 - sparse_categorical_accuracy: 0.9878 - scaled_adversarial_loss: 0.0780 - val_loss: 0.0727 - val_sparse_categorical_crossentropy: 0.0315 - val_sparse_categorical_accuracy: 0.9909 - val_scaled_adversarial_loss: 0.0412\n",
      "Epoch 489/1000\n",
      "12/12 [==============================] - 4s 355ms/step - loss: 0.1197 - sparse_categorical_crossentropy: 0.0422 - sparse_categorical_accuracy: 0.9879 - scaled_adversarial_loss: 0.0775 - val_loss: 0.0785 - val_sparse_categorical_crossentropy: 0.0329 - val_sparse_categorical_accuracy: 0.9909 - val_scaled_adversarial_loss: 0.0455\n",
      "Epoch 490/1000\n",
      "12/12 [==============================] - 4s 370ms/step - loss: 0.1155 - sparse_categorical_crossentropy: 0.0414 - sparse_categorical_accuracy: 0.9858 - scaled_adversarial_loss: 0.0742 - val_loss: 0.0703 - val_sparse_categorical_crossentropy: 0.0280 - val_sparse_categorical_accuracy: 0.9916 - val_scaled_adversarial_loss: 0.0423\n",
      "Epoch 491/1000\n",
      "12/12 [==============================] - 5s 403ms/step - loss: 0.1206 - sparse_categorical_crossentropy: 0.0441 - sparse_categorical_accuracy: 0.9848 - scaled_adversarial_loss: 0.0765 - val_loss: 0.0721 - val_sparse_categorical_crossentropy: 0.0280 - val_sparse_categorical_accuracy: 0.9902 - val_scaled_adversarial_loss: 0.0441\n",
      "Epoch 492/1000\n",
      "12/12 [==============================] - 4s 366ms/step - loss: 0.1160 - sparse_categorical_crossentropy: 0.0412 - sparse_categorical_accuracy: 0.9839 - scaled_adversarial_loss: 0.0747 - val_loss: 0.0873 - val_sparse_categorical_crossentropy: 0.0317 - val_sparse_categorical_accuracy: 0.9888 - val_scaled_adversarial_loss: 0.0556\n",
      "Epoch 493/1000\n",
      "12/12 [==============================] - 5s 424ms/step - loss: 0.1164 - sparse_categorical_crossentropy: 0.0404 - sparse_categorical_accuracy: 0.9881 - scaled_adversarial_loss: 0.0760 - val_loss: 0.0803 - val_sparse_categorical_crossentropy: 0.0286 - val_sparse_categorical_accuracy: 0.9902 - val_scaled_adversarial_loss: 0.0516\n",
      "Epoch 494/1000\n",
      "12/12 [==============================] - 5s 402ms/step - loss: 0.1113 - sparse_categorical_crossentropy: 0.0410 - sparse_categorical_accuracy: 0.9883 - scaled_adversarial_loss: 0.0703 - val_loss: 0.0770 - val_sparse_categorical_crossentropy: 0.0318 - val_sparse_categorical_accuracy: 0.9895 - val_scaled_adversarial_loss: 0.0452\n",
      "Epoch 495/1000\n",
      "12/12 [==============================] - 5s 395ms/step - loss: 0.1134 - sparse_categorical_crossentropy: 0.0402 - sparse_categorical_accuracy: 0.9844 - scaled_adversarial_loss: 0.0733 - val_loss: 0.0872 - val_sparse_categorical_crossentropy: 0.0427 - val_sparse_categorical_accuracy: 0.9888 - val_scaled_adversarial_loss: 0.0445\n",
      "Epoch 496/1000\n",
      "12/12 [==============================] - 5s 451ms/step - loss: 0.1139 - sparse_categorical_crossentropy: 0.0417 - sparse_categorical_accuracy: 0.9869 - scaled_adversarial_loss: 0.0722 - val_loss: 0.0808 - val_sparse_categorical_crossentropy: 0.0296 - val_sparse_categorical_accuracy: 0.9909 - val_scaled_adversarial_loss: 0.0513\n",
      "Epoch 497/1000\n",
      "12/12 [==============================] - 5s 392ms/step - loss: 0.1238 - sparse_categorical_crossentropy: 0.0427 - sparse_categorical_accuracy: 0.9862 - scaled_adversarial_loss: 0.0811 - val_loss: 0.0925 - val_sparse_categorical_crossentropy: 0.0314 - val_sparse_categorical_accuracy: 0.9916 - val_scaled_adversarial_loss: 0.0612\n",
      "Epoch 498/1000\n",
      "12/12 [==============================] - 5s 403ms/step - loss: 0.1204 - sparse_categorical_crossentropy: 0.0424 - sparse_categorical_accuracy: 0.9848 - scaled_adversarial_loss: 0.0780 - val_loss: 0.0748 - val_sparse_categorical_crossentropy: 0.0313 - val_sparse_categorical_accuracy: 0.9888 - val_scaled_adversarial_loss: 0.0435\n",
      "Epoch 499/1000\n",
      "12/12 [==============================] - 4s 373ms/step - loss: 0.1185 - sparse_categorical_crossentropy: 0.0435 - sparse_categorical_accuracy: 0.9841 - scaled_adversarial_loss: 0.0750 - val_loss: 0.0771 - val_sparse_categorical_crossentropy: 0.0362 - val_sparse_categorical_accuracy: 0.9895 - val_scaled_adversarial_loss: 0.0409\n",
      "Epoch 500/1000\n",
      "12/12 [==============================] - 6s 479ms/step - loss: 0.1131 - sparse_categorical_crossentropy: 0.0406 - sparse_categorical_accuracy: 0.9853 - scaled_adversarial_loss: 0.0725 - val_loss: 0.0906 - val_sparse_categorical_crossentropy: 0.0386 - val_sparse_categorical_accuracy: 0.9867 - val_scaled_adversarial_loss: 0.0520\n",
      "Epoch 501/1000\n",
      "12/12 [==============================] - 5s 409ms/step - loss: 0.1145 - sparse_categorical_crossentropy: 0.0454 - sparse_categorical_accuracy: 0.9832 - scaled_adversarial_loss: 0.0692 - val_loss: 0.0762 - val_sparse_categorical_crossentropy: 0.0300 - val_sparse_categorical_accuracy: 0.9916 - val_scaled_adversarial_loss: 0.0462\n",
      "Epoch 502/1000\n",
      "12/12 [==============================] - 5s 388ms/step - loss: 0.1248 - sparse_categorical_crossentropy: 0.0478 - sparse_categorical_accuracy: 0.9809 - scaled_adversarial_loss: 0.0770 - val_loss: 0.0693 - val_sparse_categorical_crossentropy: 0.0322 - val_sparse_categorical_accuracy: 0.9909 - val_scaled_adversarial_loss: 0.0371\n",
      "Epoch 503/1000\n",
      "12/12 [==============================] - 5s 385ms/step - loss: 0.1148 - sparse_categorical_crossentropy: 0.0408 - sparse_categorical_accuracy: 0.9865 - scaled_adversarial_loss: 0.0741 - val_loss: 0.0769 - val_sparse_categorical_crossentropy: 0.0359 - val_sparse_categorical_accuracy: 0.9923 - val_scaled_adversarial_loss: 0.0410\n",
      "Epoch 504/1000\n",
      "12/12 [==============================] - 5s 410ms/step - loss: 0.1105 - sparse_categorical_crossentropy: 0.0368 - sparse_categorical_accuracy: 0.9878 - scaled_adversarial_loss: 0.0736 - val_loss: 0.0884 - val_sparse_categorical_crossentropy: 0.0361 - val_sparse_categorical_accuracy: 0.9916 - val_scaled_adversarial_loss: 0.0522\n",
      "Epoch 505/1000\n",
      "12/12 [==============================] - 4s 370ms/step - loss: 0.1114 - sparse_categorical_crossentropy: 0.0391 - sparse_categorical_accuracy: 0.9857 - scaled_adversarial_loss: 0.0724 - val_loss: 0.0869 - val_sparse_categorical_crossentropy: 0.0372 - val_sparse_categorical_accuracy: 0.9902 - val_scaled_adversarial_loss: 0.0497\n",
      "Epoch 506/1000\n",
      "12/12 [==============================] - 5s 421ms/step - loss: 0.1119 - sparse_categorical_crossentropy: 0.0357 - sparse_categorical_accuracy: 0.9867 - scaled_adversarial_loss: 0.0762 - val_loss: 0.0839 - val_sparse_categorical_crossentropy: 0.0349 - val_sparse_categorical_accuracy: 0.9895 - val_scaled_adversarial_loss: 0.0490\n",
      "Epoch 507/1000\n",
      "12/12 [==============================] - 5s 430ms/step - loss: 0.1120 - sparse_categorical_crossentropy: 0.0352 - sparse_categorical_accuracy: 0.9888 - scaled_adversarial_loss: 0.0768 - val_loss: 0.0794 - val_sparse_categorical_crossentropy: 0.0303 - val_sparse_categorical_accuracy: 0.9909 - val_scaled_adversarial_loss: 0.0491\n",
      "Epoch 508/1000\n",
      "12/12 [==============================] - 4s 368ms/step - loss: 0.1137 - sparse_categorical_crossentropy: 0.0380 - sparse_categorical_accuracy: 0.9864 - scaled_adversarial_loss: 0.0757 - val_loss: 0.0827 - val_sparse_categorical_crossentropy: 0.0334 - val_sparse_categorical_accuracy: 0.9916 - val_scaled_adversarial_loss: 0.0493\n",
      "Epoch 509/1000\n",
      "12/12 [==============================] - 6s 486ms/step - loss: 0.1168 - sparse_categorical_crossentropy: 0.0419 - sparse_categorical_accuracy: 0.9825 - scaled_adversarial_loss: 0.0749 - val_loss: 0.0837 - val_sparse_categorical_crossentropy: 0.0399 - val_sparse_categorical_accuracy: 0.9881 - val_scaled_adversarial_loss: 0.0438\n",
      "Epoch 510/1000\n",
      "12/12 [==============================] - 5s 430ms/step - loss: 0.1137 - sparse_categorical_crossentropy: 0.0395 - sparse_categorical_accuracy: 0.9867 - scaled_adversarial_loss: 0.0742 - val_loss: 0.0761 - val_sparse_categorical_crossentropy: 0.0311 - val_sparse_categorical_accuracy: 0.9902 - val_scaled_adversarial_loss: 0.0450\n",
      "Epoch 511/1000\n",
      "12/12 [==============================] - 5s 405ms/step - loss: 0.1122 - sparse_categorical_crossentropy: 0.0353 - sparse_categorical_accuracy: 0.9869 - scaled_adversarial_loss: 0.0768 - val_loss: 0.0841 - val_sparse_categorical_crossentropy: 0.0284 - val_sparse_categorical_accuracy: 0.9909 - val_scaled_adversarial_loss: 0.0557\n",
      "Epoch 512/1000\n",
      "12/12 [==============================] - 6s 481ms/step - loss: 0.1088 - sparse_categorical_crossentropy: 0.0346 - sparse_categorical_accuracy: 0.9869 - scaled_adversarial_loss: 0.0743 - val_loss: 0.0910 - val_sparse_categorical_crossentropy: 0.0305 - val_sparse_categorical_accuracy: 0.9923 - val_scaled_adversarial_loss: 0.0605\n",
      "Epoch 513/1000\n",
      "12/12 [==============================] - 5s 385ms/step - loss: 0.1187 - sparse_categorical_crossentropy: 0.0370 - sparse_categorical_accuracy: 0.9869 - scaled_adversarial_loss: 0.0817 - val_loss: 0.0773 - val_sparse_categorical_crossentropy: 0.0324 - val_sparse_categorical_accuracy: 0.9909 - val_scaled_adversarial_loss: 0.0448\n",
      "Epoch 514/1000\n",
      "12/12 [==============================] - 6s 469ms/step - loss: 0.1087 - sparse_categorical_crossentropy: 0.0342 - sparse_categorical_accuracy: 0.9879 - scaled_adversarial_loss: 0.0745 - val_loss: 0.0745 - val_sparse_categorical_crossentropy: 0.0326 - val_sparse_categorical_accuracy: 0.9895 - val_scaled_adversarial_loss: 0.0419\n",
      "Epoch 515/1000\n",
      "12/12 [==============================] - 5s 420ms/step - loss: 0.1233 - sparse_categorical_crossentropy: 0.0440 - sparse_categorical_accuracy: 0.9834 - scaled_adversarial_loss: 0.0793 - val_loss: 0.0878 - val_sparse_categorical_crossentropy: 0.0305 - val_sparse_categorical_accuracy: 0.9895 - val_scaled_adversarial_loss: 0.0572\n",
      "Epoch 516/1000\n",
      "12/12 [==============================] - 5s 435ms/step - loss: 0.1140 - sparse_categorical_crossentropy: 0.0412 - sparse_categorical_accuracy: 0.9855 - scaled_adversarial_loss: 0.0728 - val_loss: 0.0829 - val_sparse_categorical_crossentropy: 0.0341 - val_sparse_categorical_accuracy: 0.9888 - val_scaled_adversarial_loss: 0.0488\n",
      "Epoch 517/1000\n",
      "12/12 [==============================] - 5s 401ms/step - loss: 0.1104 - sparse_categorical_crossentropy: 0.0389 - sparse_categorical_accuracy: 0.9869 - scaled_adversarial_loss: 0.0715 - val_loss: 0.0818 - val_sparse_categorical_crossentropy: 0.0320 - val_sparse_categorical_accuracy: 0.9909 - val_scaled_adversarial_loss: 0.0498\n",
      "Epoch 518/1000\n",
      "12/12 [==============================] - 5s 457ms/step - loss: 0.1089 - sparse_categorical_crossentropy: 0.0333 - sparse_categorical_accuracy: 0.9872 - scaled_adversarial_loss: 0.0756 - val_loss: 0.0861 - val_sparse_categorical_crossentropy: 0.0340 - val_sparse_categorical_accuracy: 0.9895 - val_scaled_adversarial_loss: 0.0521\n",
      "Epoch 519/1000\n",
      "12/12 [==============================] - 5s 444ms/step - loss: 0.1069 - sparse_categorical_crossentropy: 0.0324 - sparse_categorical_accuracy: 0.9893 - scaled_adversarial_loss: 0.0745 - val_loss: 0.0799 - val_sparse_categorical_crossentropy: 0.0278 - val_sparse_categorical_accuracy: 0.9916 - val_scaled_adversarial_loss: 0.0521\n",
      "Epoch 520/1000\n",
      "12/12 [==============================] - 4s 365ms/step - loss: 0.1063 - sparse_categorical_crossentropy: 0.0353 - sparse_categorical_accuracy: 0.9892 - scaled_adversarial_loss: 0.0710 - val_loss: 0.0753 - val_sparse_categorical_crossentropy: 0.0299 - val_sparse_categorical_accuracy: 0.9916 - val_scaled_adversarial_loss: 0.0455\n",
      "Epoch 521/1000\n",
      "12/12 [==============================] - 5s 453ms/step - loss: 0.1098 - sparse_categorical_crossentropy: 0.0365 - sparse_categorical_accuracy: 0.9872 - scaled_adversarial_loss: 0.0733 - val_loss: 0.0768 - val_sparse_categorical_crossentropy: 0.0298 - val_sparse_categorical_accuracy: 0.9937 - val_scaled_adversarial_loss: 0.0469\n",
      "Epoch 522/1000\n",
      "12/12 [==============================] - 5s 419ms/step - loss: 0.1139 - sparse_categorical_crossentropy: 0.0336 - sparse_categorical_accuracy: 0.9874 - scaled_adversarial_loss: 0.0803 - val_loss: 0.0863 - val_sparse_categorical_crossentropy: 0.0380 - val_sparse_categorical_accuracy: 0.9895 - val_scaled_adversarial_loss: 0.0483\n",
      "Epoch 523/1000\n",
      "12/12 [==============================] - 5s 399ms/step - loss: 0.1200 - sparse_categorical_crossentropy: 0.0428 - sparse_categorical_accuracy: 0.9862 - scaled_adversarial_loss: 0.0772 - val_loss: 0.0786 - val_sparse_categorical_crossentropy: 0.0318 - val_sparse_categorical_accuracy: 0.9923 - val_scaled_adversarial_loss: 0.0469\n",
      "Epoch 524/1000\n",
      "12/12 [==============================] - 5s 468ms/step - loss: 0.1148 - sparse_categorical_crossentropy: 0.0410 - sparse_categorical_accuracy: 0.9850 - scaled_adversarial_loss: 0.0738 - val_loss: 0.0706 - val_sparse_categorical_crossentropy: 0.0276 - val_sparse_categorical_accuracy: 0.9930 - val_scaled_adversarial_loss: 0.0431\n",
      "Epoch 525/1000\n",
      "12/12 [==============================] - 5s 400ms/step - loss: 0.1051 - sparse_categorical_crossentropy: 0.0332 - sparse_categorical_accuracy: 0.9897 - scaled_adversarial_loss: 0.0720 - val_loss: 0.0702 - val_sparse_categorical_crossentropy: 0.0269 - val_sparse_categorical_accuracy: 0.9916 - val_scaled_adversarial_loss: 0.0433\n",
      "Epoch 526/1000\n",
      "12/12 [==============================] - 5s 426ms/step - loss: 0.0995 - sparse_categorical_crossentropy: 0.0283 - sparse_categorical_accuracy: 0.9902 - scaled_adversarial_loss: 0.0712 - val_loss: 0.0761 - val_sparse_categorical_crossentropy: 0.0309 - val_sparse_categorical_accuracy: 0.9930 - val_scaled_adversarial_loss: 0.0452\n",
      "Epoch 527/1000\n",
      "12/12 [==============================] - 5s 432ms/step - loss: 0.1208 - sparse_categorical_crossentropy: 0.0409 - sparse_categorical_accuracy: 0.9867 - scaled_adversarial_loss: 0.0799 - val_loss: 0.0749 - val_sparse_categorical_crossentropy: 0.0301 - val_sparse_categorical_accuracy: 0.9923 - val_scaled_adversarial_loss: 0.0448\n",
      "Epoch 528/1000\n",
      "12/12 [==============================] - 5s 460ms/step - loss: 0.1144 - sparse_categorical_crossentropy: 0.0409 - sparse_categorical_accuracy: 0.9879 - scaled_adversarial_loss: 0.0735 - val_loss: 0.0785 - val_sparse_categorical_crossentropy: 0.0318 - val_sparse_categorical_accuracy: 0.9902 - val_scaled_adversarial_loss: 0.0467\n",
      "Epoch 529/1000\n",
      "12/12 [==============================] - 5s 408ms/step - loss: 0.1130 - sparse_categorical_crossentropy: 0.0422 - sparse_categorical_accuracy: 0.9864 - scaled_adversarial_loss: 0.0708 - val_loss: 0.0725 - val_sparse_categorical_crossentropy: 0.0306 - val_sparse_categorical_accuracy: 0.9923 - val_scaled_adversarial_loss: 0.0418\n",
      "Epoch 530/1000\n",
      "12/12 [==============================] - 5s 397ms/step - loss: 0.1152 - sparse_categorical_crossentropy: 0.0395 - sparse_categorical_accuracy: 0.9874 - scaled_adversarial_loss: 0.0756 - val_loss: 0.0894 - val_sparse_categorical_crossentropy: 0.0343 - val_sparse_categorical_accuracy: 0.9895 - val_scaled_adversarial_loss: 0.0551\n",
      "Epoch 531/1000\n",
      "12/12 [==============================] - 5s 407ms/step - loss: 0.1109 - sparse_categorical_crossentropy: 0.0356 - sparse_categorical_accuracy: 0.9879 - scaled_adversarial_loss: 0.0753 - val_loss: 0.0860 - val_sparse_categorical_crossentropy: 0.0301 - val_sparse_categorical_accuracy: 0.9923 - val_scaled_adversarial_loss: 0.0559\n",
      "Epoch 532/1000\n",
      "12/12 [==============================] - 5s 413ms/step - loss: 0.1188 - sparse_categorical_crossentropy: 0.0422 - sparse_categorical_accuracy: 0.9865 - scaled_adversarial_loss: 0.0766 - val_loss: 0.1003 - val_sparse_categorical_crossentropy: 0.0453 - val_sparse_categorical_accuracy: 0.9867 - val_scaled_adversarial_loss: 0.0550\n",
      "Epoch 533/1000\n",
      "12/12 [==============================] - 5s 446ms/step - loss: 0.1236 - sparse_categorical_crossentropy: 0.0457 - sparse_categorical_accuracy: 0.9836 - scaled_adversarial_loss: 0.0779 - val_loss: 0.0837 - val_sparse_categorical_crossentropy: 0.0301 - val_sparse_categorical_accuracy: 0.9916 - val_scaled_adversarial_loss: 0.0535\n",
      "Epoch 534/1000\n",
      "12/12 [==============================] - 5s 422ms/step - loss: 0.1169 - sparse_categorical_crossentropy: 0.0394 - sparse_categorical_accuracy: 0.9860 - scaled_adversarial_loss: 0.0776 - val_loss: 0.0920 - val_sparse_categorical_crossentropy: 0.0377 - val_sparse_categorical_accuracy: 0.9888 - val_scaled_adversarial_loss: 0.0543\n",
      "Epoch 535/1000\n",
      "12/12 [==============================] - 5s 406ms/step - loss: 0.1196 - sparse_categorical_crossentropy: 0.0411 - sparse_categorical_accuracy: 0.9865 - scaled_adversarial_loss: 0.0785 - val_loss: 0.0924 - val_sparse_categorical_crossentropy: 0.0344 - val_sparse_categorical_accuracy: 0.9902 - val_scaled_adversarial_loss: 0.0580\n",
      "Epoch 536/1000\n",
      "12/12 [==============================] - 6s 485ms/step - loss: 0.1120 - sparse_categorical_crossentropy: 0.0353 - sparse_categorical_accuracy: 0.9865 - scaled_adversarial_loss: 0.0767 - val_loss: 0.0752 - val_sparse_categorical_crossentropy: 0.0263 - val_sparse_categorical_accuracy: 0.9909 - val_scaled_adversarial_loss: 0.0489\n",
      "Epoch 537/1000\n",
      "12/12 [==============================] - 5s 419ms/step - loss: 0.1079 - sparse_categorical_crossentropy: 0.0344 - sparse_categorical_accuracy: 0.9879 - scaled_adversarial_loss: 0.0735 - val_loss: 0.0728 - val_sparse_categorical_crossentropy: 0.0268 - val_sparse_categorical_accuracy: 0.9916 - val_scaled_adversarial_loss: 0.0460\n",
      "Epoch 538/1000\n",
      "12/12 [==============================] - 5s 410ms/step - loss: 0.1143 - sparse_categorical_crossentropy: 0.0398 - sparse_categorical_accuracy: 0.9858 - scaled_adversarial_loss: 0.0745 - val_loss: 0.1113 - val_sparse_categorical_crossentropy: 0.0513 - val_sparse_categorical_accuracy: 0.9825 - val_scaled_adversarial_loss: 0.0600\n",
      "Epoch 539/1000\n",
      "12/12 [==============================] - 5s 435ms/step - loss: 0.1368 - sparse_categorical_crossentropy: 0.0501 - sparse_categorical_accuracy: 0.9834 - scaled_adversarial_loss: 0.0868 - val_loss: 0.0940 - val_sparse_categorical_crossentropy: 0.0313 - val_sparse_categorical_accuracy: 0.9923 - val_scaled_adversarial_loss: 0.0627\n",
      "Epoch 540/1000\n",
      "12/12 [==============================] - 5s 407ms/step - loss: 0.1151 - sparse_categorical_crossentropy: 0.0378 - sparse_categorical_accuracy: 0.9860 - scaled_adversarial_loss: 0.0774 - val_loss: 0.0738 - val_sparse_categorical_crossentropy: 0.0312 - val_sparse_categorical_accuracy: 0.9902 - val_scaled_adversarial_loss: 0.0426\n",
      "Epoch 541/1000\n",
      "12/12 [==============================] - 5s 402ms/step - loss: 0.1148 - sparse_categorical_crossentropy: 0.0369 - sparse_categorical_accuracy: 0.9886 - scaled_adversarial_loss: 0.0779 - val_loss: 0.0748 - val_sparse_categorical_crossentropy: 0.0310 - val_sparse_categorical_accuracy: 0.9909 - val_scaled_adversarial_loss: 0.0438\n",
      "Epoch 542/1000\n",
      "12/12 [==============================] - 5s 389ms/step - loss: 0.1179 - sparse_categorical_crossentropy: 0.0369 - sparse_categorical_accuracy: 0.9878 - scaled_adversarial_loss: 0.0811 - val_loss: 0.0788 - val_sparse_categorical_crossentropy: 0.0285 - val_sparse_categorical_accuracy: 0.9902 - val_scaled_adversarial_loss: 0.0504\n",
      "Epoch 543/1000\n",
      "12/12 [==============================] - 5s 440ms/step - loss: 0.1197 - sparse_categorical_crossentropy: 0.0472 - sparse_categorical_accuracy: 0.9843 - scaled_adversarial_loss: 0.0725 - val_loss: 0.0786 - val_sparse_categorical_crossentropy: 0.0292 - val_sparse_categorical_accuracy: 0.9895 - val_scaled_adversarial_loss: 0.0494\n",
      "Epoch 544/1000\n",
      "12/12 [==============================] - 5s 395ms/step - loss: 0.1205 - sparse_categorical_crossentropy: 0.0443 - sparse_categorical_accuracy: 0.9834 - scaled_adversarial_loss: 0.0762 - val_loss: 0.0832 - val_sparse_categorical_crossentropy: 0.0293 - val_sparse_categorical_accuracy: 0.9930 - val_scaled_adversarial_loss: 0.0539\n",
      "Epoch 545/1000\n",
      "12/12 [==============================] - 5s 423ms/step - loss: 0.1176 - sparse_categorical_crossentropy: 0.0422 - sparse_categorical_accuracy: 0.9837 - scaled_adversarial_loss: 0.0754 - val_loss: 0.0744 - val_sparse_categorical_crossentropy: 0.0352 - val_sparse_categorical_accuracy: 0.9888 - val_scaled_adversarial_loss: 0.0392\n",
      "Epoch 546/1000\n",
      "12/12 [==============================] - 5s 417ms/step - loss: 0.1159 - sparse_categorical_crossentropy: 0.0437 - sparse_categorical_accuracy: 0.9848 - scaled_adversarial_loss: 0.0722 - val_loss: 0.0834 - val_sparse_categorical_crossentropy: 0.0399 - val_sparse_categorical_accuracy: 0.9895 - val_scaled_adversarial_loss: 0.0435\n",
      "Epoch 547/1000\n",
      "12/12 [==============================] - 5s 392ms/step - loss: 0.1209 - sparse_categorical_crossentropy: 0.0424 - sparse_categorical_accuracy: 0.9860 - scaled_adversarial_loss: 0.0785 - val_loss: 0.0806 - val_sparse_categorical_crossentropy: 0.0281 - val_sparse_categorical_accuracy: 0.9923 - val_scaled_adversarial_loss: 0.0526\n",
      "Epoch 548/1000\n",
      "12/12 [==============================] - 5s 397ms/step - loss: 0.1162 - sparse_categorical_crossentropy: 0.0390 - sparse_categorical_accuracy: 0.9869 - scaled_adversarial_loss: 0.0772 - val_loss: 0.0769 - val_sparse_categorical_crossentropy: 0.0282 - val_sparse_categorical_accuracy: 0.9902 - val_scaled_adversarial_loss: 0.0487\n",
      "Epoch 549/1000\n",
      "12/12 [==============================] - 4s 342ms/step - loss: 0.1095 - sparse_categorical_crossentropy: 0.0371 - sparse_categorical_accuracy: 0.9876 - scaled_adversarial_loss: 0.0725 - val_loss: 0.0842 - val_sparse_categorical_crossentropy: 0.0314 - val_sparse_categorical_accuracy: 0.9909 - val_scaled_adversarial_loss: 0.0528\n",
      "Epoch 550/1000\n",
      "12/12 [==============================] - 4s 363ms/step - loss: 0.1138 - sparse_categorical_crossentropy: 0.0395 - sparse_categorical_accuracy: 0.9851 - scaled_adversarial_loss: 0.0743 - val_loss: 0.0885 - val_sparse_categorical_crossentropy: 0.0363 - val_sparse_categorical_accuracy: 0.9923 - val_scaled_adversarial_loss: 0.0522\n",
      "Epoch 551/1000\n",
      "12/12 [==============================] - 4s 359ms/step - loss: 0.1157 - sparse_categorical_crossentropy: 0.0400 - sparse_categorical_accuracy: 0.9885 - scaled_adversarial_loss: 0.0757 - val_loss: 0.0804 - val_sparse_categorical_crossentropy: 0.0294 - val_sparse_categorical_accuracy: 0.9909 - val_scaled_adversarial_loss: 0.0511\n",
      "Epoch 552/1000\n",
      "12/12 [==============================] - 5s 435ms/step - loss: 0.1138 - sparse_categorical_crossentropy: 0.0345 - sparse_categorical_accuracy: 0.9874 - scaled_adversarial_loss: 0.0794 - val_loss: 0.0799 - val_sparse_categorical_crossentropy: 0.0301 - val_sparse_categorical_accuracy: 0.9902 - val_scaled_adversarial_loss: 0.0499\n",
      "Epoch 553/1000\n",
      "12/12 [==============================] - 5s 375ms/step - loss: 0.1105 - sparse_categorical_crossentropy: 0.0367 - sparse_categorical_accuracy: 0.9876 - scaled_adversarial_loss: 0.0738 - val_loss: 0.0707 - val_sparse_categorical_crossentropy: 0.0278 - val_sparse_categorical_accuracy: 0.9923 - val_scaled_adversarial_loss: 0.0429\n",
      "Epoch 554/1000\n",
      "12/12 [==============================] - 5s 398ms/step - loss: 0.1051 - sparse_categorical_crossentropy: 0.0308 - sparse_categorical_accuracy: 0.9893 - scaled_adversarial_loss: 0.0743 - val_loss: 0.0720 - val_sparse_categorical_crossentropy: 0.0288 - val_sparse_categorical_accuracy: 0.9923 - val_scaled_adversarial_loss: 0.0432\n",
      "Epoch 555/1000\n",
      "12/12 [==============================] - 5s 437ms/step - loss: 0.1001 - sparse_categorical_crossentropy: 0.0298 - sparse_categorical_accuracy: 0.9885 - scaled_adversarial_loss: 0.0703 - val_loss: 0.0762 - val_sparse_categorical_crossentropy: 0.0316 - val_sparse_categorical_accuracy: 0.9909 - val_scaled_adversarial_loss: 0.0446\n",
      "Epoch 556/1000\n",
      "12/12 [==============================] - 4s 347ms/step - loss: 0.1099 - sparse_categorical_crossentropy: 0.0355 - sparse_categorical_accuracy: 0.9872 - scaled_adversarial_loss: 0.0744 - val_loss: 0.0813 - val_sparse_categorical_crossentropy: 0.0307 - val_sparse_categorical_accuracy: 0.9909 - val_scaled_adversarial_loss: 0.0506\n",
      "Epoch 557/1000\n",
      "12/12 [==============================] - 5s 432ms/step - loss: 0.1063 - sparse_categorical_crossentropy: 0.0329 - sparse_categorical_accuracy: 0.9886 - scaled_adversarial_loss: 0.0734 - val_loss: 0.0911 - val_sparse_categorical_crossentropy: 0.0447 - val_sparse_categorical_accuracy: 0.9881 - val_scaled_adversarial_loss: 0.0463\n",
      "Epoch 558/1000\n",
      "12/12 [==============================] - 5s 416ms/step - loss: 0.1057 - sparse_categorical_crossentropy: 0.0331 - sparse_categorical_accuracy: 0.9874 - scaled_adversarial_loss: 0.0726 - val_loss: 0.0848 - val_sparse_categorical_crossentropy: 0.0358 - val_sparse_categorical_accuracy: 0.9895 - val_scaled_adversarial_loss: 0.0490\n",
      "Epoch 559/1000\n",
      "12/12 [==============================] - 5s 419ms/step - loss: 0.1087 - sparse_categorical_crossentropy: 0.0371 - sparse_categorical_accuracy: 0.9872 - scaled_adversarial_loss: 0.0716 - val_loss: 0.0929 - val_sparse_categorical_crossentropy: 0.0374 - val_sparse_categorical_accuracy: 0.9881 - val_scaled_adversarial_loss: 0.0555\n",
      "Epoch 560/1000\n",
      "12/12 [==============================] - 5s 418ms/step - loss: 0.1117 - sparse_categorical_crossentropy: 0.0392 - sparse_categorical_accuracy: 0.9867 - scaled_adversarial_loss: 0.0725 - val_loss: 0.0810 - val_sparse_categorical_crossentropy: 0.0340 - val_sparse_categorical_accuracy: 0.9902 - val_scaled_adversarial_loss: 0.0470\n",
      "Epoch 561/1000\n",
      "12/12 [==============================] - 4s 369ms/step - loss: 0.1082 - sparse_categorical_crossentropy: 0.0344 - sparse_categorical_accuracy: 0.9874 - scaled_adversarial_loss: 0.0738 - val_loss: 0.0866 - val_sparse_categorical_crossentropy: 0.0313 - val_sparse_categorical_accuracy: 0.9930 - val_scaled_adversarial_loss: 0.0553\n",
      "Epoch 562/1000\n",
      "12/12 [==============================] - 5s 415ms/step - loss: 0.1023 - sparse_categorical_crossentropy: 0.0297 - sparse_categorical_accuracy: 0.9878 - scaled_adversarial_loss: 0.0726 - val_loss: 0.0775 - val_sparse_categorical_crossentropy: 0.0313 - val_sparse_categorical_accuracy: 0.9916 - val_scaled_adversarial_loss: 0.0462\n",
      "Epoch 563/1000\n",
      "12/12 [==============================] - 5s 394ms/step - loss: 0.1144 - sparse_categorical_crossentropy: 0.0392 - sparse_categorical_accuracy: 0.9879 - scaled_adversarial_loss: 0.0753 - val_loss: 0.1057 - val_sparse_categorical_crossentropy: 0.0562 - val_sparse_categorical_accuracy: 0.9874 - val_scaled_adversarial_loss: 0.0495\n",
      "Epoch 564/1000\n",
      "12/12 [==============================] - 5s 389ms/step - loss: 0.1575 - sparse_categorical_crossentropy: 0.0734 - sparse_categorical_accuracy: 0.9725 - scaled_adversarial_loss: 0.0841 - val_loss: 0.0990 - val_sparse_categorical_crossentropy: 0.0387 - val_sparse_categorical_accuracy: 0.9839 - val_scaled_adversarial_loss: 0.0603\n",
      "Epoch 565/1000\n",
      "12/12 [==============================] - 5s 400ms/step - loss: 0.1275 - sparse_categorical_crossentropy: 0.0518 - sparse_categorical_accuracy: 0.9829 - scaled_adversarial_loss: 0.0757 - val_loss: 0.0995 - val_sparse_categorical_crossentropy: 0.0291 - val_sparse_categorical_accuracy: 0.9902 - val_scaled_adversarial_loss: 0.0704\n",
      "Epoch 566/1000\n",
      "12/12 [==============================] - 4s 374ms/step - loss: 0.1222 - sparse_categorical_crossentropy: 0.0404 - sparse_categorical_accuracy: 0.9855 - scaled_adversarial_loss: 0.0818 - val_loss: 0.0923 - val_sparse_categorical_crossentropy: 0.0352 - val_sparse_categorical_accuracy: 0.9895 - val_scaled_adversarial_loss: 0.0570\n",
      "Epoch 567/1000\n",
      "12/12 [==============================] - 4s 371ms/step - loss: 0.1115 - sparse_categorical_crossentropy: 0.0348 - sparse_categorical_accuracy: 0.9864 - scaled_adversarial_loss: 0.0766 - val_loss: 0.0731 - val_sparse_categorical_crossentropy: 0.0301 - val_sparse_categorical_accuracy: 0.9916 - val_scaled_adversarial_loss: 0.0430\n",
      "Epoch 568/1000\n",
      "12/12 [==============================] - 4s 374ms/step - loss: 0.1252 - sparse_categorical_crossentropy: 0.0487 - sparse_categorical_accuracy: 0.9878 - scaled_adversarial_loss: 0.0764 - val_loss: 0.0901 - val_sparse_categorical_crossentropy: 0.0320 - val_sparse_categorical_accuracy: 0.9923 - val_scaled_adversarial_loss: 0.0581\n",
      "Epoch 569/1000\n",
      "12/12 [==============================] - 5s 393ms/step - loss: 0.1164 - sparse_categorical_crossentropy: 0.0381 - sparse_categorical_accuracy: 0.9892 - scaled_adversarial_loss: 0.0783 - val_loss: 0.0837 - val_sparse_categorical_crossentropy: 0.0295 - val_sparse_categorical_accuracy: 0.9902 - val_scaled_adversarial_loss: 0.0543\n",
      "Epoch 570/1000\n",
      "12/12 [==============================] - 5s 420ms/step - loss: 0.1183 - sparse_categorical_crossentropy: 0.0398 - sparse_categorical_accuracy: 0.9871 - scaled_adversarial_loss: 0.0786 - val_loss: 0.0849 - val_sparse_categorical_crossentropy: 0.0305 - val_sparse_categorical_accuracy: 0.9909 - val_scaled_adversarial_loss: 0.0544\n",
      "Epoch 571/1000\n",
      "12/12 [==============================] - 5s 459ms/step - loss: 0.1137 - sparse_categorical_crossentropy: 0.0377 - sparse_categorical_accuracy: 0.9876 - scaled_adversarial_loss: 0.0760 - val_loss: 0.0738 - val_sparse_categorical_crossentropy: 0.0297 - val_sparse_categorical_accuracy: 0.9930 - val_scaled_adversarial_loss: 0.0442\n",
      "Epoch 572/1000\n",
      "12/12 [==============================] - 5s 435ms/step - loss: 0.1025 - sparse_categorical_crossentropy: 0.0301 - sparse_categorical_accuracy: 0.9902 - scaled_adversarial_loss: 0.0724 - val_loss: 0.0775 - val_sparse_categorical_crossentropy: 0.0343 - val_sparse_categorical_accuracy: 0.9888 - val_scaled_adversarial_loss: 0.0432\n",
      "Epoch 573/1000\n",
      "12/12 [==============================] - 5s 428ms/step - loss: 0.1065 - sparse_categorical_crossentropy: 0.0351 - sparse_categorical_accuracy: 0.9888 - scaled_adversarial_loss: 0.0714 - val_loss: 0.0820 - val_sparse_categorical_crossentropy: 0.0335 - val_sparse_categorical_accuracy: 0.9916 - val_scaled_adversarial_loss: 0.0486\n",
      "Epoch 574/1000\n",
      "12/12 [==============================] - 5s 427ms/step - loss: 0.1077 - sparse_categorical_crossentropy: 0.0337 - sparse_categorical_accuracy: 0.9900 - scaled_adversarial_loss: 0.0739 - val_loss: 0.0888 - val_sparse_categorical_crossentropy: 0.0420 - val_sparse_categorical_accuracy: 0.9874 - val_scaled_adversarial_loss: 0.0469\n",
      "Epoch 575/1000\n",
      "12/12 [==============================] - 5s 436ms/step - loss: 0.1295 - sparse_categorical_crossentropy: 0.0472 - sparse_categorical_accuracy: 0.9827 - scaled_adversarial_loss: 0.0823 - val_loss: 0.0963 - val_sparse_categorical_crossentropy: 0.0367 - val_sparse_categorical_accuracy: 0.9888 - val_scaled_adversarial_loss: 0.0596\n",
      "Epoch 576/1000\n",
      "12/12 [==============================] - 6s 482ms/step - loss: 0.1201 - sparse_categorical_crossentropy: 0.0354 - sparse_categorical_accuracy: 0.9881 - scaled_adversarial_loss: 0.0846 - val_loss: 0.0847 - val_sparse_categorical_crossentropy: 0.0327 - val_sparse_categorical_accuracy: 0.9902 - val_scaled_adversarial_loss: 0.0520\n",
      "Epoch 577/1000\n",
      "12/12 [==============================] - 6s 498ms/step - loss: 0.1164 - sparse_categorical_crossentropy: 0.0406 - sparse_categorical_accuracy: 0.9857 - scaled_adversarial_loss: 0.0758 - val_loss: 0.0769 - val_sparse_categorical_crossentropy: 0.0318 - val_sparse_categorical_accuracy: 0.9930 - val_scaled_adversarial_loss: 0.0451\n",
      "Epoch 578/1000\n",
      "12/12 [==============================] - 4s 377ms/step - loss: 0.1127 - sparse_categorical_crossentropy: 0.0390 - sparse_categorical_accuracy: 0.9865 - scaled_adversarial_loss: 0.0737 - val_loss: 0.0815 - val_sparse_categorical_crossentropy: 0.0378 - val_sparse_categorical_accuracy: 0.9888 - val_scaled_adversarial_loss: 0.0436\n",
      "Epoch 579/1000\n",
      "12/12 [==============================] - 4s 364ms/step - loss: 0.1087 - sparse_categorical_crossentropy: 0.0379 - sparse_categorical_accuracy: 0.9864 - scaled_adversarial_loss: 0.0708 - val_loss: 0.0780 - val_sparse_categorical_crossentropy: 0.0323 - val_sparse_categorical_accuracy: 0.9881 - val_scaled_adversarial_loss: 0.0458\n",
      "Epoch 580/1000\n",
      "12/12 [==============================] - 4s 358ms/step - loss: 0.1115 - sparse_categorical_crossentropy: 0.0357 - sparse_categorical_accuracy: 0.9864 - scaled_adversarial_loss: 0.0758 - val_loss: 0.0734 - val_sparse_categorical_crossentropy: 0.0326 - val_sparse_categorical_accuracy: 0.9916 - val_scaled_adversarial_loss: 0.0407\n",
      "Epoch 581/1000\n",
      "12/12 [==============================] - 4s 367ms/step - loss: 0.1120 - sparse_categorical_crossentropy: 0.0375 - sparse_categorical_accuracy: 0.9878 - scaled_adversarial_loss: 0.0745 - val_loss: 0.0835 - val_sparse_categorical_crossentropy: 0.0374 - val_sparse_categorical_accuracy: 0.9888 - val_scaled_adversarial_loss: 0.0461\n",
      "Epoch 582/1000\n",
      "12/12 [==============================] - 4s 373ms/step - loss: 0.1253 - sparse_categorical_crossentropy: 0.0472 - sparse_categorical_accuracy: 0.9864 - scaled_adversarial_loss: 0.0781 - val_loss: 0.0995 - val_sparse_categorical_crossentropy: 0.0490 - val_sparse_categorical_accuracy: 0.9832 - val_scaled_adversarial_loss: 0.0505\n",
      "Epoch 583/1000\n",
      "12/12 [==============================] - 4s 381ms/step - loss: 0.1335 - sparse_categorical_crossentropy: 0.0526 - sparse_categorical_accuracy: 0.9808 - scaled_adversarial_loss: 0.0809 - val_loss: 0.0896 - val_sparse_categorical_crossentropy: 0.0376 - val_sparse_categorical_accuracy: 0.9902 - val_scaled_adversarial_loss: 0.0520\n",
      "Epoch 584/1000\n",
      "12/12 [==============================] - 4s 367ms/step - loss: 0.1311 - sparse_categorical_crossentropy: 0.0545 - sparse_categorical_accuracy: 0.9837 - scaled_adversarial_loss: 0.0766 - val_loss: 0.0940 - val_sparse_categorical_crossentropy: 0.0332 - val_sparse_categorical_accuracy: 0.9909 - val_scaled_adversarial_loss: 0.0608\n",
      "Epoch 585/1000\n",
      "12/12 [==============================] - 4s 365ms/step - loss: 0.1184 - sparse_categorical_crossentropy: 0.0427 - sparse_categorical_accuracy: 0.9851 - scaled_adversarial_loss: 0.0757 - val_loss: 0.0757 - val_sparse_categorical_crossentropy: 0.0301 - val_sparse_categorical_accuracy: 0.9937 - val_scaled_adversarial_loss: 0.0455\n",
      "Epoch 586/1000\n",
      "12/12 [==============================] - 4s 359ms/step - loss: 0.1014 - sparse_categorical_crossentropy: 0.0308 - sparse_categorical_accuracy: 0.9899 - scaled_adversarial_loss: 0.0706 - val_loss: 0.0812 - val_sparse_categorical_crossentropy: 0.0304 - val_sparse_categorical_accuracy: 0.9930 - val_scaled_adversarial_loss: 0.0508\n",
      "Epoch 587/1000\n",
      "12/12 [==============================] - 4s 379ms/step - loss: 0.1099 - sparse_categorical_crossentropy: 0.0351 - sparse_categorical_accuracy: 0.9881 - scaled_adversarial_loss: 0.0748 - val_loss: 0.0823 - val_sparse_categorical_crossentropy: 0.0281 - val_sparse_categorical_accuracy: 0.9930 - val_scaled_adversarial_loss: 0.0542\n",
      "Epoch 588/1000\n",
      "12/12 [==============================] - 5s 402ms/step - loss: 0.1103 - sparse_categorical_crossentropy: 0.0313 - sparse_categorical_accuracy: 0.9900 - scaled_adversarial_loss: 0.0790 - val_loss: 0.0837 - val_sparse_categorical_crossentropy: 0.0341 - val_sparse_categorical_accuracy: 0.9909 - val_scaled_adversarial_loss: 0.0495\n",
      "Epoch 589/1000\n",
      "12/12 [==============================] - 5s 398ms/step - loss: 0.1047 - sparse_categorical_crossentropy: 0.0302 - sparse_categorical_accuracy: 0.9906 - scaled_adversarial_loss: 0.0746 - val_loss: 0.0822 - val_sparse_categorical_crossentropy: 0.0317 - val_sparse_categorical_accuracy: 0.9909 - val_scaled_adversarial_loss: 0.0505\n",
      "Epoch 590/1000\n",
      "12/12 [==============================] - 5s 410ms/step - loss: 0.1037 - sparse_categorical_crossentropy: 0.0303 - sparse_categorical_accuracy: 0.9883 - scaled_adversarial_loss: 0.0734 - val_loss: 0.0830 - val_sparse_categorical_crossentropy: 0.0356 - val_sparse_categorical_accuracy: 0.9902 - val_scaled_adversarial_loss: 0.0473\n",
      "Epoch 591/1000\n",
      "12/12 [==============================] - 5s 415ms/step - loss: 0.1008 - sparse_categorical_crossentropy: 0.0305 - sparse_categorical_accuracy: 0.9895 - scaled_adversarial_loss: 0.0703 - val_loss: 0.0791 - val_sparse_categorical_crossentropy: 0.0310 - val_sparse_categorical_accuracy: 0.9902 - val_scaled_adversarial_loss: 0.0482\n",
      "Epoch 592/1000\n",
      "12/12 [==============================] - 4s 377ms/step - loss: 0.1143 - sparse_categorical_crossentropy: 0.0401 - sparse_categorical_accuracy: 0.9886 - scaled_adversarial_loss: 0.0742 - val_loss: 0.0835 - val_sparse_categorical_crossentropy: 0.0323 - val_sparse_categorical_accuracy: 0.9881 - val_scaled_adversarial_loss: 0.0511\n",
      "Epoch 593/1000\n",
      "12/12 [==============================] - 4s 366ms/step - loss: 0.1089 - sparse_categorical_crossentropy: 0.0356 - sparse_categorical_accuracy: 0.9876 - scaled_adversarial_loss: 0.0733 - val_loss: 0.0858 - val_sparse_categorical_crossentropy: 0.0351 - val_sparse_categorical_accuracy: 0.9888 - val_scaled_adversarial_loss: 0.0508\n",
      "Epoch 594/1000\n",
      "12/12 [==============================] - 5s 391ms/step - loss: 0.1042 - sparse_categorical_crossentropy: 0.0313 - sparse_categorical_accuracy: 0.9888 - scaled_adversarial_loss: 0.0730 - val_loss: 0.0910 - val_sparse_categorical_crossentropy: 0.0399 - val_sparse_categorical_accuracy: 0.9909 - val_scaled_adversarial_loss: 0.0511\n",
      "Epoch 595/1000\n",
      "12/12 [==============================] - 4s 373ms/step - loss: 0.1116 - sparse_categorical_crossentropy: 0.0382 - sparse_categorical_accuracy: 0.9874 - scaled_adversarial_loss: 0.0735 - val_loss: 0.0823 - val_sparse_categorical_crossentropy: 0.0378 - val_sparse_categorical_accuracy: 0.9895 - val_scaled_adversarial_loss: 0.0444\n",
      "Epoch 596/1000\n",
      "12/12 [==============================] - 5s 413ms/step - loss: 0.1086 - sparse_categorical_crossentropy: 0.0338 - sparse_categorical_accuracy: 0.9879 - scaled_adversarial_loss: 0.0748 - val_loss: 0.0756 - val_sparse_categorical_crossentropy: 0.0346 - val_sparse_categorical_accuracy: 0.9909 - val_scaled_adversarial_loss: 0.0409\n",
      "Epoch 597/1000\n",
      "12/12 [==============================] - 5s 383ms/step - loss: 0.1062 - sparse_categorical_crossentropy: 0.0304 - sparse_categorical_accuracy: 0.9888 - scaled_adversarial_loss: 0.0759 - val_loss: 0.0831 - val_sparse_categorical_crossentropy: 0.0380 - val_sparse_categorical_accuracy: 0.9909 - val_scaled_adversarial_loss: 0.0450\n",
      "Epoch 598/1000\n",
      "12/12 [==============================] - 5s 382ms/step - loss: 0.1031 - sparse_categorical_crossentropy: 0.0350 - sparse_categorical_accuracy: 0.9879 - scaled_adversarial_loss: 0.0681 - val_loss: 0.0858 - val_sparse_categorical_crossentropy: 0.0324 - val_sparse_categorical_accuracy: 0.9923 - val_scaled_adversarial_loss: 0.0534\n",
      "Epoch 599/1000\n",
      "12/12 [==============================] - 4s 376ms/step - loss: 0.1078 - sparse_categorical_crossentropy: 0.0324 - sparse_categorical_accuracy: 0.9890 - scaled_adversarial_loss: 0.0754 - val_loss: 0.0828 - val_sparse_categorical_crossentropy: 0.0369 - val_sparse_categorical_accuracy: 0.9902 - val_scaled_adversarial_loss: 0.0459\n",
      "Epoch 600/1000\n",
      "12/12 [==============================] - 4s 372ms/step - loss: 0.1024 - sparse_categorical_crossentropy: 0.0312 - sparse_categorical_accuracy: 0.9902 - scaled_adversarial_loss: 0.0712 - val_loss: 0.0828 - val_sparse_categorical_crossentropy: 0.0366 - val_sparse_categorical_accuracy: 0.9895 - val_scaled_adversarial_loss: 0.0462\n",
      "Epoch 601/1000\n",
      "12/12 [==============================] - 5s 404ms/step - loss: 0.1070 - sparse_categorical_crossentropy: 0.0317 - sparse_categorical_accuracy: 0.9900 - scaled_adversarial_loss: 0.0753 - val_loss: 0.0896 - val_sparse_categorical_crossentropy: 0.0396 - val_sparse_categorical_accuracy: 0.9881 - val_scaled_adversarial_loss: 0.0500\n",
      "Epoch 602/1000\n",
      "12/12 [==============================] - 5s 392ms/step - loss: 0.1092 - sparse_categorical_crossentropy: 0.0374 - sparse_categorical_accuracy: 0.9876 - scaled_adversarial_loss: 0.0719 - val_loss: 0.0823 - val_sparse_categorical_crossentropy: 0.0364 - val_sparse_categorical_accuracy: 0.9874 - val_scaled_adversarial_loss: 0.0459\n",
      "Epoch 603/1000\n",
      "12/12 [==============================] - 5s 394ms/step - loss: 0.1054 - sparse_categorical_crossentropy: 0.0346 - sparse_categorical_accuracy: 0.9890 - scaled_adversarial_loss: 0.0708 - val_loss: 0.0797 - val_sparse_categorical_crossentropy: 0.0309 - val_sparse_categorical_accuracy: 0.9902 - val_scaled_adversarial_loss: 0.0487\n",
      "Epoch 604/1000\n",
      "12/12 [==============================] - 5s 405ms/step - loss: 0.1197 - sparse_categorical_crossentropy: 0.0409 - sparse_categorical_accuracy: 0.9851 - scaled_adversarial_loss: 0.0788 - val_loss: 0.0945 - val_sparse_categorical_crossentropy: 0.0340 - val_sparse_categorical_accuracy: 0.9916 - val_scaled_adversarial_loss: 0.0605\n",
      "Epoch 605/1000\n",
      "12/12 [==============================] - 5s 421ms/step - loss: 0.1069 - sparse_categorical_crossentropy: 0.0357 - sparse_categorical_accuracy: 0.9900 - scaled_adversarial_loss: 0.0712 - val_loss: 0.1135 - val_sparse_categorical_crossentropy: 0.0554 - val_sparse_categorical_accuracy: 0.9860 - val_scaled_adversarial_loss: 0.0581\n",
      "Epoch 606/1000\n",
      "12/12 [==============================] - 5s 415ms/step - loss: 0.1417 - sparse_categorical_crossentropy: 0.0571 - sparse_categorical_accuracy: 0.9822 - scaled_adversarial_loss: 0.0846 - val_loss: 0.0993 - val_sparse_categorical_crossentropy: 0.0443 - val_sparse_categorical_accuracy: 0.9888 - val_scaled_adversarial_loss: 0.0550\n",
      "Epoch 607/1000\n",
      "12/12 [==============================] - 5s 390ms/step - loss: 0.1233 - sparse_categorical_crossentropy: 0.0463 - sparse_categorical_accuracy: 0.9857 - scaled_adversarial_loss: 0.0771 - val_loss: 0.1172 - val_sparse_categorical_crossentropy: 0.0461 - val_sparse_categorical_accuracy: 0.9881 - val_scaled_adversarial_loss: 0.0710\n",
      "Epoch 608/1000\n",
      "12/12 [==============================] - 4s 367ms/step - loss: 0.1239 - sparse_categorical_crossentropy: 0.0453 - sparse_categorical_accuracy: 0.9857 - scaled_adversarial_loss: 0.0787 - val_loss: 0.0878 - val_sparse_categorical_crossentropy: 0.0340 - val_sparse_categorical_accuracy: 0.9902 - val_scaled_adversarial_loss: 0.0539\n",
      "Epoch 609/1000\n",
      "12/12 [==============================] - 4s 365ms/step - loss: 0.1154 - sparse_categorical_crossentropy: 0.0414 - sparse_categorical_accuracy: 0.9862 - scaled_adversarial_loss: 0.0740 - val_loss: 0.0872 - val_sparse_categorical_crossentropy: 0.0337 - val_sparse_categorical_accuracy: 0.9909 - val_scaled_adversarial_loss: 0.0535\n",
      "Epoch 610/1000\n",
      "12/12 [==============================] - 4s 361ms/step - loss: 0.1141 - sparse_categorical_crossentropy: 0.0426 - sparse_categorical_accuracy: 0.9865 - scaled_adversarial_loss: 0.0715 - val_loss: 0.0826 - val_sparse_categorical_crossentropy: 0.0305 - val_sparse_categorical_accuracy: 0.9916 - val_scaled_adversarial_loss: 0.0520\n",
      "Epoch 611/1000\n",
      "12/12 [==============================] - 4s 367ms/step - loss: 0.1196 - sparse_categorical_crossentropy: 0.0417 - sparse_categorical_accuracy: 0.9864 - scaled_adversarial_loss: 0.0779 - val_loss: 0.0876 - val_sparse_categorical_crossentropy: 0.0362 - val_sparse_categorical_accuracy: 0.9902 - val_scaled_adversarial_loss: 0.0514\n",
      "Epoch 612/1000\n",
      "12/12 [==============================] - 5s 385ms/step - loss: 0.1092 - sparse_categorical_crossentropy: 0.0349 - sparse_categorical_accuracy: 0.9886 - scaled_adversarial_loss: 0.0743 - val_loss: 0.0939 - val_sparse_categorical_crossentropy: 0.0415 - val_sparse_categorical_accuracy: 0.9874 - val_scaled_adversarial_loss: 0.0524\n",
      "Epoch 613/1000\n",
      "12/12 [==============================] - 5s 382ms/step - loss: 0.1101 - sparse_categorical_crossentropy: 0.0370 - sparse_categorical_accuracy: 0.9846 - scaled_adversarial_loss: 0.0731 - val_loss: 0.0973 - val_sparse_categorical_crossentropy: 0.0571 - val_sparse_categorical_accuracy: 0.9846 - val_scaled_adversarial_loss: 0.0402\n",
      "Epoch 614/1000\n",
      "12/12 [==============================] - 5s 410ms/step - loss: 0.1206 - sparse_categorical_crossentropy: 0.0429 - sparse_categorical_accuracy: 0.9844 - scaled_adversarial_loss: 0.0776 - val_loss: 0.0813 - val_sparse_categorical_crossentropy: 0.0355 - val_sparse_categorical_accuracy: 0.9888 - val_scaled_adversarial_loss: 0.0458\n",
      "Epoch 615/1000\n",
      "12/12 [==============================] - 5s 399ms/step - loss: 0.1095 - sparse_categorical_crossentropy: 0.0345 - sparse_categorical_accuracy: 0.9869 - scaled_adversarial_loss: 0.0750 - val_loss: 0.0730 - val_sparse_categorical_crossentropy: 0.0312 - val_sparse_categorical_accuracy: 0.9909 - val_scaled_adversarial_loss: 0.0419\n",
      "Epoch 616/1000\n",
      "12/12 [==============================] - 5s 400ms/step - loss: 0.1094 - sparse_categorical_crossentropy: 0.0319 - sparse_categorical_accuracy: 0.9885 - scaled_adversarial_loss: 0.0775 - val_loss: 0.0760 - val_sparse_categorical_crossentropy: 0.0328 - val_sparse_categorical_accuracy: 0.9888 - val_scaled_adversarial_loss: 0.0432\n",
      "Epoch 617/1000\n",
      "12/12 [==============================] - 6s 471ms/step - loss: 0.1135 - sparse_categorical_crossentropy: 0.0419 - sparse_categorical_accuracy: 0.9855 - scaled_adversarial_loss: 0.0716 - val_loss: 0.0923 - val_sparse_categorical_crossentropy: 0.0346 - val_sparse_categorical_accuracy: 0.9895 - val_scaled_adversarial_loss: 0.0577\n",
      "Epoch 618/1000\n",
      "12/12 [==============================] - 5s 463ms/step - loss: 0.1116 - sparse_categorical_crossentropy: 0.0381 - sparse_categorical_accuracy: 0.9874 - scaled_adversarial_loss: 0.0735 - val_loss: 0.0737 - val_sparse_categorical_crossentropy: 0.0285 - val_sparse_categorical_accuracy: 0.9937 - val_scaled_adversarial_loss: 0.0452\n",
      "Epoch 619/1000\n",
      "12/12 [==============================] - 6s 476ms/step - loss: 0.1179 - sparse_categorical_crossentropy: 0.0440 - sparse_categorical_accuracy: 0.9874 - scaled_adversarial_loss: 0.0739 - val_loss: 0.0788 - val_sparse_categorical_crossentropy: 0.0293 - val_sparse_categorical_accuracy: 0.9909 - val_scaled_adversarial_loss: 0.0494\n",
      "Epoch 620/1000\n",
      "12/12 [==============================] - 5s 452ms/step - loss: 0.1152 - sparse_categorical_crossentropy: 0.0360 - sparse_categorical_accuracy: 0.9906 - scaled_adversarial_loss: 0.0792 - val_loss: 0.0839 - val_sparse_categorical_crossentropy: 0.0261 - val_sparse_categorical_accuracy: 0.9916 - val_scaled_adversarial_loss: 0.0578\n",
      "Epoch 621/1000\n",
      "12/12 [==============================] - 5s 420ms/step - loss: 0.1091 - sparse_categorical_crossentropy: 0.0324 - sparse_categorical_accuracy: 0.9886 - scaled_adversarial_loss: 0.0766 - val_loss: 0.0922 - val_sparse_categorical_crossentropy: 0.0308 - val_sparse_categorical_accuracy: 0.9923 - val_scaled_adversarial_loss: 0.0614\n",
      "Epoch 622/1000\n",
      "12/12 [==============================] - 6s 504ms/step - loss: 0.1092 - sparse_categorical_crossentropy: 0.0319 - sparse_categorical_accuracy: 0.9888 - scaled_adversarial_loss: 0.0772 - val_loss: 0.0806 - val_sparse_categorical_crossentropy: 0.0280 - val_sparse_categorical_accuracy: 0.9937 - val_scaled_adversarial_loss: 0.0525\n",
      "Epoch 623/1000\n",
      "12/12 [==============================] - 6s 519ms/step - loss: 0.1121 - sparse_categorical_crossentropy: 0.0334 - sparse_categorical_accuracy: 0.9876 - scaled_adversarial_loss: 0.0787 - val_loss: 0.0801 - val_sparse_categorical_crossentropy: 0.0280 - val_sparse_categorical_accuracy: 0.9902 - val_scaled_adversarial_loss: 0.0520\n",
      "Epoch 624/1000\n",
      "12/12 [==============================] - 6s 519ms/step - loss: 0.1121 - sparse_categorical_crossentropy: 0.0369 - sparse_categorical_accuracy: 0.9900 - scaled_adversarial_loss: 0.0752 - val_loss: 0.0827 - val_sparse_categorical_crossentropy: 0.0286 - val_sparse_categorical_accuracy: 0.9888 - val_scaled_adversarial_loss: 0.0542\n",
      "Epoch 625/1000\n",
      "12/12 [==============================] - 6s 492ms/step - loss: 0.1095 - sparse_categorical_crossentropy: 0.0328 - sparse_categorical_accuracy: 0.9872 - scaled_adversarial_loss: 0.0768 - val_loss: 0.0841 - val_sparse_categorical_crossentropy: 0.0347 - val_sparse_categorical_accuracy: 0.9881 - val_scaled_adversarial_loss: 0.0494\n",
      "Epoch 626/1000\n",
      "12/12 [==============================] - 6s 491ms/step - loss: 0.1059 - sparse_categorical_crossentropy: 0.0328 - sparse_categorical_accuracy: 0.9897 - scaled_adversarial_loss: 0.0731 - val_loss: 0.0930 - val_sparse_categorical_crossentropy: 0.0347 - val_sparse_categorical_accuracy: 0.9916 - val_scaled_adversarial_loss: 0.0583\n",
      "Epoch 627/1000\n",
      "12/12 [==============================] - 6s 493ms/step - loss: 0.1108 - sparse_categorical_crossentropy: 0.0350 - sparse_categorical_accuracy: 0.9892 - scaled_adversarial_loss: 0.0758 - val_loss: 0.0989 - val_sparse_categorical_crossentropy: 0.0341 - val_sparse_categorical_accuracy: 0.9888 - val_scaled_adversarial_loss: 0.0648\n",
      "Epoch 628/1000\n",
      "12/12 [==============================] - 7s 547ms/step - loss: 0.1189 - sparse_categorical_crossentropy: 0.0372 - sparse_categorical_accuracy: 0.9888 - scaled_adversarial_loss: 0.0817 - val_loss: 0.0773 - val_sparse_categorical_crossentropy: 0.0319 - val_sparse_categorical_accuracy: 0.9895 - val_scaled_adversarial_loss: 0.0454\n",
      "Epoch 629/1000\n",
      "12/12 [==============================] - 6s 478ms/step - loss: 0.1147 - sparse_categorical_crossentropy: 0.0380 - sparse_categorical_accuracy: 0.9885 - scaled_adversarial_loss: 0.0767 - val_loss: 0.0939 - val_sparse_categorical_crossentropy: 0.0338 - val_sparse_categorical_accuracy: 0.9881 - val_scaled_adversarial_loss: 0.0600\n",
      "Epoch 630/1000\n",
      "12/12 [==============================] - 6s 504ms/step - loss: 0.1203 - sparse_categorical_crossentropy: 0.0439 - sparse_categorical_accuracy: 0.9860 - scaled_adversarial_loss: 0.0764 - val_loss: 0.0835 - val_sparse_categorical_crossentropy: 0.0306 - val_sparse_categorical_accuracy: 0.9888 - val_scaled_adversarial_loss: 0.0528\n",
      "Epoch 631/1000\n",
      "12/12 [==============================] - 6s 474ms/step - loss: 0.1068 - sparse_categorical_crossentropy: 0.0349 - sparse_categorical_accuracy: 0.9871 - scaled_adversarial_loss: 0.0719 - val_loss: 0.0845 - val_sparse_categorical_crossentropy: 0.0296 - val_sparse_categorical_accuracy: 0.9916 - val_scaled_adversarial_loss: 0.0549\n",
      "Epoch 632/1000\n",
      "12/12 [==============================] - 5s 457ms/step - loss: 0.1206 - sparse_categorical_crossentropy: 0.0437 - sparse_categorical_accuracy: 0.9878 - scaled_adversarial_loss: 0.0768 - val_loss: 0.0804 - val_sparse_categorical_crossentropy: 0.0324 - val_sparse_categorical_accuracy: 0.9895 - val_scaled_adversarial_loss: 0.0481\n",
      "Epoch 633/1000\n",
      "12/12 [==============================] - 4s 348ms/step - loss: 0.1214 - sparse_categorical_crossentropy: 0.0403 - sparse_categorical_accuracy: 0.9879 - scaled_adversarial_loss: 0.0811 - val_loss: 0.0781 - val_sparse_categorical_crossentropy: 0.0289 - val_sparse_categorical_accuracy: 0.9923 - val_scaled_adversarial_loss: 0.0492\n",
      "Epoch 634/1000\n",
      "12/12 [==============================] - 5s 382ms/step - loss: 0.1077 - sparse_categorical_crossentropy: 0.0349 - sparse_categorical_accuracy: 0.9879 - scaled_adversarial_loss: 0.0728 - val_loss: 0.0767 - val_sparse_categorical_crossentropy: 0.0332 - val_sparse_categorical_accuracy: 0.9923 - val_scaled_adversarial_loss: 0.0435\n",
      "Epoch 635/1000\n",
      "12/12 [==============================] - 4s 375ms/step - loss: 0.1049 - sparse_categorical_crossentropy: 0.0339 - sparse_categorical_accuracy: 0.9886 - scaled_adversarial_loss: 0.0710 - val_loss: 0.0881 - val_sparse_categorical_crossentropy: 0.0350 - val_sparse_categorical_accuracy: 0.9909 - val_scaled_adversarial_loss: 0.0531\n",
      "Epoch 636/1000\n",
      "12/12 [==============================] - 5s 382ms/step - loss: 0.1102 - sparse_categorical_crossentropy: 0.0364 - sparse_categorical_accuracy: 0.9869 - scaled_adversarial_loss: 0.0738 - val_loss: 0.0738 - val_sparse_categorical_crossentropy: 0.0344 - val_sparse_categorical_accuracy: 0.9909 - val_scaled_adversarial_loss: 0.0394\n",
      "Epoch 637/1000\n",
      "12/12 [==============================] - 6s 470ms/step - loss: 0.1002 - sparse_categorical_crossentropy: 0.0310 - sparse_categorical_accuracy: 0.9892 - scaled_adversarial_loss: 0.0692 - val_loss: 0.0799 - val_sparse_categorical_crossentropy: 0.0362 - val_sparse_categorical_accuracy: 0.9902 - val_scaled_adversarial_loss: 0.0437\n",
      "Epoch 638/1000\n",
      "12/12 [==============================] - 5s 426ms/step - loss: 0.1062 - sparse_categorical_crossentropy: 0.0340 - sparse_categorical_accuracy: 0.9902 - scaled_adversarial_loss: 0.0722 - val_loss: 0.0805 - val_sparse_categorical_crossentropy: 0.0382 - val_sparse_categorical_accuracy: 0.9909 - val_scaled_adversarial_loss: 0.0423\n",
      "Epoch 639/1000\n",
      "12/12 [==============================] - 5s 420ms/step - loss: 0.1093 - sparse_categorical_crossentropy: 0.0335 - sparse_categorical_accuracy: 0.9881 - scaled_adversarial_loss: 0.0758 - val_loss: 0.0754 - val_sparse_categorical_crossentropy: 0.0342 - val_sparse_categorical_accuracy: 0.9923 - val_scaled_adversarial_loss: 0.0412\n",
      "Epoch 640/1000\n",
      "12/12 [==============================] - 5s 388ms/step - loss: 0.1190 - sparse_categorical_crossentropy: 0.0416 - sparse_categorical_accuracy: 0.9851 - scaled_adversarial_loss: 0.0774 - val_loss: 0.0825 - val_sparse_categorical_crossentropy: 0.0313 - val_sparse_categorical_accuracy: 0.9930 - val_scaled_adversarial_loss: 0.0512\n",
      "Epoch 641/1000\n",
      "12/12 [==============================] - 4s 358ms/step - loss: 0.1136 - sparse_categorical_crossentropy: 0.0410 - sparse_categorical_accuracy: 0.9841 - scaled_adversarial_loss: 0.0726 - val_loss: 0.0845 - val_sparse_categorical_crossentropy: 0.0334 - val_sparse_categorical_accuracy: 0.9923 - val_scaled_adversarial_loss: 0.0511\n",
      "Epoch 642/1000\n",
      "12/12 [==============================] - 4s 374ms/step - loss: 0.1073 - sparse_categorical_crossentropy: 0.0351 - sparse_categorical_accuracy: 0.9888 - scaled_adversarial_loss: 0.0722 - val_loss: 0.0838 - val_sparse_categorical_crossentropy: 0.0439 - val_sparse_categorical_accuracy: 0.9874 - val_scaled_adversarial_loss: 0.0400\n",
      "Epoch 643/1000\n",
      "12/12 [==============================] - 4s 374ms/step - loss: 0.1115 - sparse_categorical_crossentropy: 0.0406 - sparse_categorical_accuracy: 0.9865 - scaled_adversarial_loss: 0.0709 - val_loss: 0.0772 - val_sparse_categorical_crossentropy: 0.0312 - val_sparse_categorical_accuracy: 0.9902 - val_scaled_adversarial_loss: 0.0460\n",
      "Epoch 644/1000\n",
      "12/12 [==============================] - 5s 380ms/step - loss: 0.1019 - sparse_categorical_crossentropy: 0.0306 - sparse_categorical_accuracy: 0.9890 - scaled_adversarial_loss: 0.0712 - val_loss: 0.0840 - val_sparse_categorical_crossentropy: 0.0298 - val_sparse_categorical_accuracy: 0.9923 - val_scaled_adversarial_loss: 0.0542\n",
      "Epoch 645/1000\n",
      "12/12 [==============================] - 5s 379ms/step - loss: 0.1012 - sparse_categorical_crossentropy: 0.0314 - sparse_categorical_accuracy: 0.9888 - scaled_adversarial_loss: 0.0698 - val_loss: 0.0785 - val_sparse_categorical_crossentropy: 0.0337 - val_sparse_categorical_accuracy: 0.9888 - val_scaled_adversarial_loss: 0.0448\n",
      "Epoch 646/1000\n",
      "12/12 [==============================] - 5s 381ms/step - loss: 0.1022 - sparse_categorical_crossentropy: 0.0316 - sparse_categorical_accuracy: 0.9897 - scaled_adversarial_loss: 0.0705 - val_loss: 0.0785 - val_sparse_categorical_crossentropy: 0.0293 - val_sparse_categorical_accuracy: 0.9909 - val_scaled_adversarial_loss: 0.0492\n",
      "Epoch 647/1000\n",
      "12/12 [==============================] - 4s 362ms/step - loss: 0.1046 - sparse_categorical_crossentropy: 0.0344 - sparse_categorical_accuracy: 0.9892 - scaled_adversarial_loss: 0.0702 - val_loss: 0.0793 - val_sparse_categorical_crossentropy: 0.0307 - val_sparse_categorical_accuracy: 0.9895 - val_scaled_adversarial_loss: 0.0486\n",
      "Epoch 648/1000\n",
      "12/12 [==============================] - 4s 365ms/step - loss: 0.1239 - sparse_categorical_crossentropy: 0.0435 - sparse_categorical_accuracy: 0.9858 - scaled_adversarial_loss: 0.0805 - val_loss: 0.0880 - val_sparse_categorical_crossentropy: 0.0392 - val_sparse_categorical_accuracy: 0.9881 - val_scaled_adversarial_loss: 0.0487\n",
      "Epoch 649/1000\n",
      "12/12 [==============================] - 4s 371ms/step - loss: 0.1192 - sparse_categorical_crossentropy: 0.0409 - sparse_categorical_accuracy: 0.9860 - scaled_adversarial_loss: 0.0783 - val_loss: 0.0854 - val_sparse_categorical_crossentropy: 0.0324 - val_sparse_categorical_accuracy: 0.9888 - val_scaled_adversarial_loss: 0.0530\n",
      "Epoch 650/1000\n",
      "12/12 [==============================] - 5s 418ms/step - loss: 0.1003 - sparse_categorical_crossentropy: 0.0325 - sparse_categorical_accuracy: 0.9885 - scaled_adversarial_loss: 0.0677 - val_loss: 0.0941 - val_sparse_categorical_crossentropy: 0.0418 - val_sparse_categorical_accuracy: 0.9881 - val_scaled_adversarial_loss: 0.0523\n",
      "Epoch 651/1000\n",
      "12/12 [==============================] - 5s 423ms/step - loss: 0.1017 - sparse_categorical_crossentropy: 0.0310 - sparse_categorical_accuracy: 0.9897 - scaled_adversarial_loss: 0.0708 - val_loss: 0.0837 - val_sparse_categorical_crossentropy: 0.0435 - val_sparse_categorical_accuracy: 0.9874 - val_scaled_adversarial_loss: 0.0403\n",
      "Epoch 652/1000\n",
      "12/12 [==============================] - 5s 418ms/step - loss: 0.1116 - sparse_categorical_crossentropy: 0.0380 - sparse_categorical_accuracy: 0.9916 - scaled_adversarial_loss: 0.0737 - val_loss: 0.0856 - val_sparse_categorical_crossentropy: 0.0334 - val_sparse_categorical_accuracy: 0.9916 - val_scaled_adversarial_loss: 0.0522\n",
      "Epoch 653/1000\n",
      "12/12 [==============================] - 5s 409ms/step - loss: 0.1331 - sparse_categorical_crossentropy: 0.0547 - sparse_categorical_accuracy: 0.9829 - scaled_adversarial_loss: 0.0784 - val_loss: 0.1277 - val_sparse_categorical_crossentropy: 0.0476 - val_sparse_categorical_accuracy: 0.9902 - val_scaled_adversarial_loss: 0.0801\n",
      "Epoch 654/1000\n",
      "12/12 [==============================] - 4s 356ms/step - loss: 0.1280 - sparse_categorical_crossentropy: 0.0490 - sparse_categorical_accuracy: 0.9857 - scaled_adversarial_loss: 0.0790 - val_loss: 0.0778 - val_sparse_categorical_crossentropy: 0.0357 - val_sparse_categorical_accuracy: 0.9874 - val_scaled_adversarial_loss: 0.0421\n",
      "Epoch 655/1000\n",
      "12/12 [==============================] - 4s 355ms/step - loss: 0.1110 - sparse_categorical_crossentropy: 0.0372 - sparse_categorical_accuracy: 0.9885 - scaled_adversarial_loss: 0.0738 - val_loss: 0.0709 - val_sparse_categorical_crossentropy: 0.0285 - val_sparse_categorical_accuracy: 0.9895 - val_scaled_adversarial_loss: 0.0425\n",
      "Epoch 656/1000\n",
      "12/12 [==============================] - 5s 394ms/step - loss: 0.1065 - sparse_categorical_crossentropy: 0.0332 - sparse_categorical_accuracy: 0.9886 - scaled_adversarial_loss: 0.0733 - val_loss: 0.0856 - val_sparse_categorical_crossentropy: 0.0410 - val_sparse_categorical_accuracy: 0.9888 - val_scaled_adversarial_loss: 0.0446\n",
      "Epoch 657/1000\n",
      "12/12 [==============================] - 5s 399ms/step - loss: 0.1075 - sparse_categorical_crossentropy: 0.0362 - sparse_categorical_accuracy: 0.9878 - scaled_adversarial_loss: 0.0713 - val_loss: 0.0791 - val_sparse_categorical_crossentropy: 0.0341 - val_sparse_categorical_accuracy: 0.9909 - val_scaled_adversarial_loss: 0.0450\n",
      "Epoch 658/1000\n",
      "12/12 [==============================] - 5s 414ms/step - loss: 0.1162 - sparse_categorical_crossentropy: 0.0390 - sparse_categorical_accuracy: 0.9872 - scaled_adversarial_loss: 0.0771 - val_loss: 0.0710 - val_sparse_categorical_crossentropy: 0.0307 - val_sparse_categorical_accuracy: 0.9909 - val_scaled_adversarial_loss: 0.0403\n",
      "Epoch 659/1000\n",
      "12/12 [==============================] - 5s 424ms/step - loss: 0.1121 - sparse_categorical_crossentropy: 0.0361 - sparse_categorical_accuracy: 0.9888 - scaled_adversarial_loss: 0.0760 - val_loss: 0.0913 - val_sparse_categorical_crossentropy: 0.0434 - val_sparse_categorical_accuracy: 0.9881 - val_scaled_adversarial_loss: 0.0479\n",
      "Epoch 660/1000\n",
      "12/12 [==============================] - 5s 407ms/step - loss: 0.1268 - sparse_categorical_crossentropy: 0.0506 - sparse_categorical_accuracy: 0.9855 - scaled_adversarial_loss: 0.0762 - val_loss: 0.1005 - val_sparse_categorical_crossentropy: 0.0383 - val_sparse_categorical_accuracy: 0.9916 - val_scaled_adversarial_loss: 0.0622\n",
      "Epoch 661/1000\n",
      "12/12 [==============================] - 5s 451ms/step - loss: 0.1308 - sparse_categorical_crossentropy: 0.0515 - sparse_categorical_accuracy: 0.9816 - scaled_adversarial_loss: 0.0792 - val_loss: 0.0930 - val_sparse_categorical_crossentropy: 0.0347 - val_sparse_categorical_accuracy: 0.9881 - val_scaled_adversarial_loss: 0.0583\n",
      "Epoch 662/1000\n",
      "12/12 [==============================] - 5s 463ms/step - loss: 0.1144 - sparse_categorical_crossentropy: 0.0412 - sparse_categorical_accuracy: 0.9864 - scaled_adversarial_loss: 0.0732 - val_loss: 0.0756 - val_sparse_categorical_crossentropy: 0.0303 - val_sparse_categorical_accuracy: 0.9909 - val_scaled_adversarial_loss: 0.0454\n",
      "Epoch 663/1000\n",
      "12/12 [==============================] - 5s 457ms/step - loss: 0.1111 - sparse_categorical_crossentropy: 0.0331 - sparse_categorical_accuracy: 0.9893 - scaled_adversarial_loss: 0.0780 - val_loss: 0.0748 - val_sparse_categorical_crossentropy: 0.0333 - val_sparse_categorical_accuracy: 0.9916 - val_scaled_adversarial_loss: 0.0415\n",
      "Epoch 664/1000\n",
      "12/12 [==============================] - 6s 475ms/step - loss: 0.0978 - sparse_categorical_crossentropy: 0.0302 - sparse_categorical_accuracy: 0.9900 - scaled_adversarial_loss: 0.0676 - val_loss: 0.0736 - val_sparse_categorical_crossentropy: 0.0303 - val_sparse_categorical_accuracy: 0.9916 - val_scaled_adversarial_loss: 0.0433\n",
      "Epoch 665/1000\n",
      "12/12 [==============================] - 6s 484ms/step - loss: 0.1071 - sparse_categorical_crossentropy: 0.0344 - sparse_categorical_accuracy: 0.9913 - scaled_adversarial_loss: 0.0728 - val_loss: 0.0739 - val_sparse_categorical_crossentropy: 0.0330 - val_sparse_categorical_accuracy: 0.9909 - val_scaled_adversarial_loss: 0.0409\n",
      "Epoch 666/1000\n",
      "12/12 [==============================] - 5s 439ms/step - loss: 0.1077 - sparse_categorical_crossentropy: 0.0334 - sparse_categorical_accuracy: 0.9899 - scaled_adversarial_loss: 0.0743 - val_loss: 0.0812 - val_sparse_categorical_crossentropy: 0.0453 - val_sparse_categorical_accuracy: 0.9874 - val_scaled_adversarial_loss: 0.0360\n",
      "Epoch 667/1000\n",
      "12/12 [==============================] - 5s 430ms/step - loss: 0.1077 - sparse_categorical_crossentropy: 0.0368 - sparse_categorical_accuracy: 0.9869 - scaled_adversarial_loss: 0.0710 - val_loss: 0.0813 - val_sparse_categorical_crossentropy: 0.0358 - val_sparse_categorical_accuracy: 0.9916 - val_scaled_adversarial_loss: 0.0455\n",
      "Epoch 668/1000\n",
      "12/12 [==============================] - 5s 397ms/step - loss: 0.1073 - sparse_categorical_crossentropy: 0.0344 - sparse_categorical_accuracy: 0.9883 - scaled_adversarial_loss: 0.0728 - val_loss: 0.0740 - val_sparse_categorical_crossentropy: 0.0310 - val_sparse_categorical_accuracy: 0.9916 - val_scaled_adversarial_loss: 0.0430\n",
      "Epoch 669/1000\n",
      "12/12 [==============================] - 4s 367ms/step - loss: 0.1092 - sparse_categorical_crossentropy: 0.0374 - sparse_categorical_accuracy: 0.9886 - scaled_adversarial_loss: 0.0718 - val_loss: 0.0763 - val_sparse_categorical_crossentropy: 0.0323 - val_sparse_categorical_accuracy: 0.9888 - val_scaled_adversarial_loss: 0.0441\n",
      "Epoch 670/1000\n",
      "12/12 [==============================] - 4s 368ms/step - loss: 0.1095 - sparse_categorical_crossentropy: 0.0343 - sparse_categorical_accuracy: 0.9883 - scaled_adversarial_loss: 0.0752 - val_loss: 0.0694 - val_sparse_categorical_crossentropy: 0.0283 - val_sparse_categorical_accuracy: 0.9930 - val_scaled_adversarial_loss: 0.0411\n",
      "Epoch 671/1000\n",
      "12/12 [==============================] - 5s 398ms/step - loss: 0.1042 - sparse_categorical_crossentropy: 0.0336 - sparse_categorical_accuracy: 0.9902 - scaled_adversarial_loss: 0.0705 - val_loss: 0.0703 - val_sparse_categorical_crossentropy: 0.0289 - val_sparse_categorical_accuracy: 0.9916 - val_scaled_adversarial_loss: 0.0414\n",
      "Epoch 672/1000\n",
      "12/12 [==============================] - 5s 433ms/step - loss: 0.0966 - sparse_categorical_crossentropy: 0.0292 - sparse_categorical_accuracy: 0.9904 - scaled_adversarial_loss: 0.0674 - val_loss: 0.0750 - val_sparse_categorical_crossentropy: 0.0339 - val_sparse_categorical_accuracy: 0.9923 - val_scaled_adversarial_loss: 0.0411\n",
      "Epoch 673/1000\n",
      "12/12 [==============================] - 5s 439ms/step - loss: 0.1085 - sparse_categorical_crossentropy: 0.0364 - sparse_categorical_accuracy: 0.9867 - scaled_adversarial_loss: 0.0720 - val_loss: 0.0702 - val_sparse_categorical_crossentropy: 0.0306 - val_sparse_categorical_accuracy: 0.9923 - val_scaled_adversarial_loss: 0.0396\n",
      "Epoch 674/1000\n",
      "12/12 [==============================] - 5s 442ms/step - loss: 0.1097 - sparse_categorical_crossentropy: 0.0356 - sparse_categorical_accuracy: 0.9872 - scaled_adversarial_loss: 0.0741 - val_loss: 0.0752 - val_sparse_categorical_crossentropy: 0.0310 - val_sparse_categorical_accuracy: 0.9909 - val_scaled_adversarial_loss: 0.0441\n",
      "Epoch 675/1000\n",
      "12/12 [==============================] - 5s 453ms/step - loss: 0.0954 - sparse_categorical_crossentropy: 0.0250 - sparse_categorical_accuracy: 0.9920 - scaled_adversarial_loss: 0.0704 - val_loss: 0.0771 - val_sparse_categorical_crossentropy: 0.0351 - val_sparse_categorical_accuracy: 0.9888 - val_scaled_adversarial_loss: 0.0420\n",
      "Epoch 676/1000\n",
      "12/12 [==============================] - 5s 448ms/step - loss: 0.0935 - sparse_categorical_crossentropy: 0.0267 - sparse_categorical_accuracy: 0.9904 - scaled_adversarial_loss: 0.0668 - val_loss: 0.0742 - val_sparse_categorical_crossentropy: 0.0286 - val_sparse_categorical_accuracy: 0.9909 - val_scaled_adversarial_loss: 0.0456\n",
      "Epoch 677/1000\n",
      "12/12 [==============================] - 6s 468ms/step - loss: 0.1036 - sparse_categorical_crossentropy: 0.0312 - sparse_categorical_accuracy: 0.9883 - scaled_adversarial_loss: 0.0725 - val_loss: 0.0805 - val_sparse_categorical_crossentropy: 0.0285 - val_sparse_categorical_accuracy: 0.9916 - val_scaled_adversarial_loss: 0.0521\n",
      "Epoch 678/1000\n",
      "12/12 [==============================] - 6s 474ms/step - loss: 0.1043 - sparse_categorical_crossentropy: 0.0317 - sparse_categorical_accuracy: 0.9874 - scaled_adversarial_loss: 0.0726 - val_loss: 0.0829 - val_sparse_categorical_crossentropy: 0.0297 - val_sparse_categorical_accuracy: 0.9902 - val_scaled_adversarial_loss: 0.0532\n",
      "Epoch 679/1000\n",
      "12/12 [==============================] - 5s 450ms/step - loss: 0.1094 - sparse_categorical_crossentropy: 0.0369 - sparse_categorical_accuracy: 0.9885 - scaled_adversarial_loss: 0.0725 - val_loss: 0.0783 - val_sparse_categorical_crossentropy: 0.0313 - val_sparse_categorical_accuracy: 0.9909 - val_scaled_adversarial_loss: 0.0470\n",
      "Epoch 680/1000\n",
      "12/12 [==============================] - 6s 482ms/step - loss: 0.1067 - sparse_categorical_crossentropy: 0.0331 - sparse_categorical_accuracy: 0.9897 - scaled_adversarial_loss: 0.0736 - val_loss: 0.0860 - val_sparse_categorical_crossentropy: 0.0446 - val_sparse_categorical_accuracy: 0.9888 - val_scaled_adversarial_loss: 0.0415\n",
      "Epoch 681/1000\n",
      "12/12 [==============================] - 6s 501ms/step - loss: 0.1010 - sparse_categorical_crossentropy: 0.0307 - sparse_categorical_accuracy: 0.9871 - scaled_adversarial_loss: 0.0703 - val_loss: 0.0850 - val_sparse_categorical_crossentropy: 0.0451 - val_sparse_categorical_accuracy: 0.9874 - val_scaled_adversarial_loss: 0.0400\n",
      "Epoch 682/1000\n",
      "12/12 [==============================] - 6s 462ms/step - loss: 0.1085 - sparse_categorical_crossentropy: 0.0349 - sparse_categorical_accuracy: 0.9885 - scaled_adversarial_loss: 0.0736 - val_loss: 0.0861 - val_sparse_categorical_crossentropy: 0.0299 - val_sparse_categorical_accuracy: 0.9909 - val_scaled_adversarial_loss: 0.0562\n",
      "Epoch 683/1000\n",
      "12/12 [==============================] - 6s 469ms/step - loss: 0.1103 - sparse_categorical_crossentropy: 0.0385 - sparse_categorical_accuracy: 0.9879 - scaled_adversarial_loss: 0.0718 - val_loss: 0.0856 - val_sparse_categorical_crossentropy: 0.0338 - val_sparse_categorical_accuracy: 0.9909 - val_scaled_adversarial_loss: 0.0517\n",
      "Epoch 684/1000\n",
      "12/12 [==============================] - 5s 456ms/step - loss: 0.1073 - sparse_categorical_crossentropy: 0.0352 - sparse_categorical_accuracy: 0.9878 - scaled_adversarial_loss: 0.0720 - val_loss: 0.0827 - val_sparse_categorical_crossentropy: 0.0372 - val_sparse_categorical_accuracy: 0.9902 - val_scaled_adversarial_loss: 0.0455\n",
      "Epoch 685/1000\n",
      "12/12 [==============================] - 6s 487ms/step - loss: 0.1090 - sparse_categorical_crossentropy: 0.0361 - sparse_categorical_accuracy: 0.9883 - scaled_adversarial_loss: 0.0729 - val_loss: 0.0963 - val_sparse_categorical_crossentropy: 0.0389 - val_sparse_categorical_accuracy: 0.9881 - val_scaled_adversarial_loss: 0.0574\n",
      "Epoch 686/1000\n",
      "12/12 [==============================] - 6s 464ms/step - loss: 0.1124 - sparse_categorical_crossentropy: 0.0369 - sparse_categorical_accuracy: 0.9865 - scaled_adversarial_loss: 0.0755 - val_loss: 0.0827 - val_sparse_categorical_crossentropy: 0.0368 - val_sparse_categorical_accuracy: 0.9895 - val_scaled_adversarial_loss: 0.0459\n",
      "Epoch 687/1000\n",
      "12/12 [==============================] - 5s 444ms/step - loss: 0.0938 - sparse_categorical_crossentropy: 0.0260 - sparse_categorical_accuracy: 0.9911 - scaled_adversarial_loss: 0.0679 - val_loss: 0.0928 - val_sparse_categorical_crossentropy: 0.0428 - val_sparse_categorical_accuracy: 0.9867 - val_scaled_adversarial_loss: 0.0500\n",
      "Epoch 688/1000\n",
      "12/12 [==============================] - 6s 469ms/step - loss: 0.1051 - sparse_categorical_crossentropy: 0.0349 - sparse_categorical_accuracy: 0.9874 - scaled_adversarial_loss: 0.0703 - val_loss: 0.0898 - val_sparse_categorical_crossentropy: 0.0455 - val_sparse_categorical_accuracy: 0.9874 - val_scaled_adversarial_loss: 0.0443\n",
      "Epoch 689/1000\n",
      "12/12 [==============================] - 6s 467ms/step - loss: 0.1079 - sparse_categorical_crossentropy: 0.0351 - sparse_categorical_accuracy: 0.9881 - scaled_adversarial_loss: 0.0728 - val_loss: 0.0748 - val_sparse_categorical_crossentropy: 0.0341 - val_sparse_categorical_accuracy: 0.9888 - val_scaled_adversarial_loss: 0.0407\n",
      "Epoch 690/1000\n",
      "12/12 [==============================] - 5s 444ms/step - loss: 0.1121 - sparse_categorical_crossentropy: 0.0379 - sparse_categorical_accuracy: 0.9871 - scaled_adversarial_loss: 0.0742 - val_loss: 0.0854 - val_sparse_categorical_crossentropy: 0.0347 - val_sparse_categorical_accuracy: 0.9888 - val_scaled_adversarial_loss: 0.0508\n",
      "Epoch 691/1000\n",
      "12/12 [==============================] - 5s 429ms/step - loss: 0.1211 - sparse_categorical_crossentropy: 0.0455 - sparse_categorical_accuracy: 0.9843 - scaled_adversarial_loss: 0.0756 - val_loss: 0.0864 - val_sparse_categorical_crossentropy: 0.0395 - val_sparse_categorical_accuracy: 0.9881 - val_scaled_adversarial_loss: 0.0469\n",
      "Epoch 692/1000\n",
      "12/12 [==============================] - 6s 474ms/step - loss: 0.1436 - sparse_categorical_crossentropy: 0.0625 - sparse_categorical_accuracy: 0.9769 - scaled_adversarial_loss: 0.0811 - val_loss: 0.0936 - val_sparse_categorical_crossentropy: 0.0346 - val_sparse_categorical_accuracy: 0.9881 - val_scaled_adversarial_loss: 0.0590\n",
      "Epoch 693/1000\n",
      "12/12 [==============================] - 5s 457ms/step - loss: 0.1091 - sparse_categorical_crossentropy: 0.0369 - sparse_categorical_accuracy: 0.9869 - scaled_adversarial_loss: 0.0722 - val_loss: 0.0714 - val_sparse_categorical_crossentropy: 0.0329 - val_sparse_categorical_accuracy: 0.9902 - val_scaled_adversarial_loss: 0.0385\n",
      "Epoch 694/1000\n",
      "12/12 [==============================] - 5s 432ms/step - loss: 0.1016 - sparse_categorical_crossentropy: 0.0295 - sparse_categorical_accuracy: 0.9900 - scaled_adversarial_loss: 0.0721 - val_loss: 0.0929 - val_sparse_categorical_crossentropy: 0.0299 - val_sparse_categorical_accuracy: 0.9916 - val_scaled_adversarial_loss: 0.0630\n",
      "Epoch 695/1000\n",
      "12/12 [==============================] - 5s 431ms/step - loss: 0.1090 - sparse_categorical_crossentropy: 0.0358 - sparse_categorical_accuracy: 0.9888 - scaled_adversarial_loss: 0.0732 - val_loss: 0.0847 - val_sparse_categorical_crossentropy: 0.0346 - val_sparse_categorical_accuracy: 0.9888 - val_scaled_adversarial_loss: 0.0501\n",
      "Epoch 696/1000\n",
      "12/12 [==============================] - 6s 491ms/step - loss: 0.1066 - sparse_categorical_crossentropy: 0.0329 - sparse_categorical_accuracy: 0.9876 - scaled_adversarial_loss: 0.0737 - val_loss: 0.0806 - val_sparse_categorical_crossentropy: 0.0332 - val_sparse_categorical_accuracy: 0.9909 - val_scaled_adversarial_loss: 0.0475\n",
      "Epoch 697/1000\n",
      "12/12 [==============================] - 5s 456ms/step - loss: 0.1003 - sparse_categorical_crossentropy: 0.0255 - sparse_categorical_accuracy: 0.9913 - scaled_adversarial_loss: 0.0748 - val_loss: 0.0779 - val_sparse_categorical_crossentropy: 0.0319 - val_sparse_categorical_accuracy: 0.9916 - val_scaled_adversarial_loss: 0.0460\n",
      "Epoch 698/1000\n",
      "12/12 [==============================] - 4s 346ms/step - loss: 0.0956 - sparse_categorical_crossentropy: 0.0262 - sparse_categorical_accuracy: 0.9923 - scaled_adversarial_loss: 0.0693 - val_loss: 0.1007 - val_sparse_categorical_crossentropy: 0.0379 - val_sparse_categorical_accuracy: 0.9909 - val_scaled_adversarial_loss: 0.0628\n",
      "Epoch 699/1000\n",
      "12/12 [==============================] - 4s 350ms/step - loss: 0.1386 - sparse_categorical_crossentropy: 0.0551 - sparse_categorical_accuracy: 0.9836 - scaled_adversarial_loss: 0.0836 - val_loss: 0.0798 - val_sparse_categorical_crossentropy: 0.0354 - val_sparse_categorical_accuracy: 0.9881 - val_scaled_adversarial_loss: 0.0444\n",
      "Epoch 700/1000\n",
      "12/12 [==============================] - 5s 386ms/step - loss: 0.1314 - sparse_categorical_crossentropy: 0.0464 - sparse_categorical_accuracy: 0.9827 - scaled_adversarial_loss: 0.0850 - val_loss: 0.0879 - val_sparse_categorical_crossentropy: 0.0442 - val_sparse_categorical_accuracy: 0.9923 - val_scaled_adversarial_loss: 0.0437\n",
      "Epoch 701/1000\n",
      "12/12 [==============================] - 5s 380ms/step - loss: 0.1072 - sparse_categorical_crossentropy: 0.0349 - sparse_categorical_accuracy: 0.9885 - scaled_adversarial_loss: 0.0724 - val_loss: 0.0929 - val_sparse_categorical_crossentropy: 0.0322 - val_sparse_categorical_accuracy: 0.9909 - val_scaled_adversarial_loss: 0.0606\n",
      "Epoch 702/1000\n",
      "12/12 [==============================] - 5s 444ms/step - loss: 0.1059 - sparse_categorical_crossentropy: 0.0315 - sparse_categorical_accuracy: 0.9902 - scaled_adversarial_loss: 0.0744 - val_loss: 0.0972 - val_sparse_categorical_crossentropy: 0.0377 - val_sparse_categorical_accuracy: 0.9895 - val_scaled_adversarial_loss: 0.0595\n",
      "Epoch 703/1000\n",
      "12/12 [==============================] - 5s 407ms/step - loss: 0.1128 - sparse_categorical_crossentropy: 0.0344 - sparse_categorical_accuracy: 0.9878 - scaled_adversarial_loss: 0.0784 - val_loss: 0.0874 - val_sparse_categorical_crossentropy: 0.0291 - val_sparse_categorical_accuracy: 0.9909 - val_scaled_adversarial_loss: 0.0583\n",
      "Epoch 704/1000\n",
      "12/12 [==============================] - 4s 358ms/step - loss: 0.1078 - sparse_categorical_crossentropy: 0.0328 - sparse_categorical_accuracy: 0.9879 - scaled_adversarial_loss: 0.0751 - val_loss: 0.0890 - val_sparse_categorical_crossentropy: 0.0327 - val_sparse_categorical_accuracy: 0.9888 - val_scaled_adversarial_loss: 0.0563\n",
      "Epoch 705/1000\n",
      "12/12 [==============================] - 4s 375ms/step - loss: 0.1027 - sparse_categorical_crossentropy: 0.0316 - sparse_categorical_accuracy: 0.9892 - scaled_adversarial_loss: 0.0711 - val_loss: 0.0769 - val_sparse_categorical_crossentropy: 0.0299 - val_sparse_categorical_accuracy: 0.9909 - val_scaled_adversarial_loss: 0.0470\n",
      "Epoch 706/1000\n",
      "12/12 [==============================] - 4s 374ms/step - loss: 0.1109 - sparse_categorical_crossentropy: 0.0356 - sparse_categorical_accuracy: 0.9876 - scaled_adversarial_loss: 0.0753 - val_loss: 0.0887 - val_sparse_categorical_crossentropy: 0.0354 - val_sparse_categorical_accuracy: 0.9895 - val_scaled_adversarial_loss: 0.0533\n",
      "Epoch 707/1000\n",
      "12/12 [==============================] - 5s 380ms/step - loss: 0.0976 - sparse_categorical_crossentropy: 0.0258 - sparse_categorical_accuracy: 0.9904 - scaled_adversarial_loss: 0.0719 - val_loss: 0.0921 - val_sparse_categorical_crossentropy: 0.0315 - val_sparse_categorical_accuracy: 0.9916 - val_scaled_adversarial_loss: 0.0606\n",
      "Epoch 708/1000\n",
      "12/12 [==============================] - 4s 373ms/step - loss: 0.1119 - sparse_categorical_crossentropy: 0.0345 - sparse_categorical_accuracy: 0.9883 - scaled_adversarial_loss: 0.0774 - val_loss: 0.0710 - val_sparse_categorical_crossentropy: 0.0308 - val_sparse_categorical_accuracy: 0.9895 - val_scaled_adversarial_loss: 0.0402\n",
      "Epoch 709/1000\n",
      "12/12 [==============================] - 4s 373ms/step - loss: 0.1031 - sparse_categorical_crossentropy: 0.0304 - sparse_categorical_accuracy: 0.9885 - scaled_adversarial_loss: 0.0727 - val_loss: 0.0775 - val_sparse_categorical_crossentropy: 0.0390 - val_sparse_categorical_accuracy: 0.9895 - val_scaled_adversarial_loss: 0.0385\n",
      "Epoch 710/1000\n",
      "12/12 [==============================] - 5s 383ms/step - loss: 0.0979 - sparse_categorical_crossentropy: 0.0277 - sparse_categorical_accuracy: 0.9893 - scaled_adversarial_loss: 0.0702 - val_loss: 0.0669 - val_sparse_categorical_crossentropy: 0.0300 - val_sparse_categorical_accuracy: 0.9916 - val_scaled_adversarial_loss: 0.0369\n",
      "Epoch 711/1000\n",
      "12/12 [==============================] - 5s 383ms/step - loss: 0.1060 - sparse_categorical_crossentropy: 0.0321 - sparse_categorical_accuracy: 0.9885 - scaled_adversarial_loss: 0.0739 - val_loss: 0.0766 - val_sparse_categorical_crossentropy: 0.0357 - val_sparse_categorical_accuracy: 0.9916 - val_scaled_adversarial_loss: 0.0409\n",
      "Epoch 712/1000\n",
      "12/12 [==============================] - 4s 363ms/step - loss: 0.0987 - sparse_categorical_crossentropy: 0.0294 - sparse_categorical_accuracy: 0.9899 - scaled_adversarial_loss: 0.0694 - val_loss: 0.0845 - val_sparse_categorical_crossentropy: 0.0307 - val_sparse_categorical_accuracy: 0.9923 - val_scaled_adversarial_loss: 0.0539\n",
      "Epoch 713/1000\n",
      "12/12 [==============================] - 5s 381ms/step - loss: 0.1006 - sparse_categorical_crossentropy: 0.0296 - sparse_categorical_accuracy: 0.9906 - scaled_adversarial_loss: 0.0711 - val_loss: 0.0846 - val_sparse_categorical_crossentropy: 0.0293 - val_sparse_categorical_accuracy: 0.9888 - val_scaled_adversarial_loss: 0.0553\n",
      "Epoch 714/1000\n",
      "12/12 [==============================] - 4s 377ms/step - loss: 0.0998 - sparse_categorical_crossentropy: 0.0289 - sparse_categorical_accuracy: 0.9907 - scaled_adversarial_loss: 0.0709 - val_loss: 0.0715 - val_sparse_categorical_crossentropy: 0.0295 - val_sparse_categorical_accuracy: 0.9909 - val_scaled_adversarial_loss: 0.0420\n",
      "Epoch 715/1000\n",
      "12/12 [==============================] - 5s 396ms/step - loss: 0.1048 - sparse_categorical_crossentropy: 0.0335 - sparse_categorical_accuracy: 0.9907 - scaled_adversarial_loss: 0.0713 - val_loss: 0.0833 - val_sparse_categorical_crossentropy: 0.0318 - val_sparse_categorical_accuracy: 0.9902 - val_scaled_adversarial_loss: 0.0515\n",
      "Epoch 716/1000\n",
      "12/12 [==============================] - 5s 377ms/step - loss: 0.1017 - sparse_categorical_crossentropy: 0.0336 - sparse_categorical_accuracy: 0.9904 - scaled_adversarial_loss: 0.0681 - val_loss: 0.0750 - val_sparse_categorical_crossentropy: 0.0289 - val_sparse_categorical_accuracy: 0.9923 - val_scaled_adversarial_loss: 0.0461\n",
      "Epoch 717/1000\n",
      "12/12 [==============================] - 4s 362ms/step - loss: 0.1119 - sparse_categorical_crossentropy: 0.0378 - sparse_categorical_accuracy: 0.9867 - scaled_adversarial_loss: 0.0740 - val_loss: 0.0754 - val_sparse_categorical_crossentropy: 0.0315 - val_sparse_categorical_accuracy: 0.9895 - val_scaled_adversarial_loss: 0.0439\n",
      "Epoch 718/1000\n",
      "12/12 [==============================] - 4s 376ms/step - loss: 0.1066 - sparse_categorical_crossentropy: 0.0338 - sparse_categorical_accuracy: 0.9890 - scaled_adversarial_loss: 0.0727 - val_loss: 0.0685 - val_sparse_categorical_crossentropy: 0.0279 - val_sparse_categorical_accuracy: 0.9902 - val_scaled_adversarial_loss: 0.0406\n",
      "Epoch 719/1000\n",
      "12/12 [==============================] - 5s 427ms/step - loss: 0.1051 - sparse_categorical_crossentropy: 0.0352 - sparse_categorical_accuracy: 0.9890 - scaled_adversarial_loss: 0.0699 - val_loss: 0.0798 - val_sparse_categorical_crossentropy: 0.0271 - val_sparse_categorical_accuracy: 0.9909 - val_scaled_adversarial_loss: 0.0528\n",
      "Epoch 720/1000\n",
      "12/12 [==============================] - 4s 363ms/step - loss: 0.0969 - sparse_categorical_crossentropy: 0.0287 - sparse_categorical_accuracy: 0.9925 - scaled_adversarial_loss: 0.0683 - val_loss: 0.0727 - val_sparse_categorical_crossentropy: 0.0279 - val_sparse_categorical_accuracy: 0.9930 - val_scaled_adversarial_loss: 0.0448\n",
      "Epoch 721/1000\n",
      "12/12 [==============================] - 4s 362ms/step - loss: 0.1093 - sparse_categorical_crossentropy: 0.0363 - sparse_categorical_accuracy: 0.9881 - scaled_adversarial_loss: 0.0730 - val_loss: 0.0799 - val_sparse_categorical_crossentropy: 0.0371 - val_sparse_categorical_accuracy: 0.9881 - val_scaled_adversarial_loss: 0.0428\n",
      "Epoch 722/1000\n",
      "12/12 [==============================] - 4s 370ms/step - loss: 0.1081 - sparse_categorical_crossentropy: 0.0339 - sparse_categorical_accuracy: 0.9902 - scaled_adversarial_loss: 0.0741 - val_loss: 0.0729 - val_sparse_categorical_crossentropy: 0.0282 - val_sparse_categorical_accuracy: 0.9916 - val_scaled_adversarial_loss: 0.0447\n",
      "Epoch 723/1000\n",
      "12/12 [==============================] - 4s 374ms/step - loss: 0.1036 - sparse_categorical_crossentropy: 0.0322 - sparse_categorical_accuracy: 0.9904 - scaled_adversarial_loss: 0.0714 - val_loss: 0.0763 - val_sparse_categorical_crossentropy: 0.0269 - val_sparse_categorical_accuracy: 0.9923 - val_scaled_adversarial_loss: 0.0494\n",
      "Epoch 724/1000\n",
      "12/12 [==============================] - 5s 382ms/step - loss: 0.1144 - sparse_categorical_crossentropy: 0.0374 - sparse_categorical_accuracy: 0.9872 - scaled_adversarial_loss: 0.0769 - val_loss: 0.0833 - val_sparse_categorical_crossentropy: 0.0314 - val_sparse_categorical_accuracy: 0.9923 - val_scaled_adversarial_loss: 0.0518\n",
      "Epoch 725/1000\n",
      "12/12 [==============================] - 4s 367ms/step - loss: 0.1175 - sparse_categorical_crossentropy: 0.0425 - sparse_categorical_accuracy: 0.9850 - scaled_adversarial_loss: 0.0750 - val_loss: 0.0818 - val_sparse_categorical_crossentropy: 0.0322 - val_sparse_categorical_accuracy: 0.9916 - val_scaled_adversarial_loss: 0.0496\n",
      "Epoch 726/1000\n",
      "12/12 [==============================] - 4s 359ms/step - loss: 0.1108 - sparse_categorical_crossentropy: 0.0369 - sparse_categorical_accuracy: 0.9865 - scaled_adversarial_loss: 0.0739 - val_loss: 0.0728 - val_sparse_categorical_crossentropy: 0.0297 - val_sparse_categorical_accuracy: 0.9909 - val_scaled_adversarial_loss: 0.0432\n",
      "Epoch 727/1000\n",
      "12/12 [==============================] - 5s 427ms/step - loss: 0.1177 - sparse_categorical_crossentropy: 0.0444 - sparse_categorical_accuracy: 0.9851 - scaled_adversarial_loss: 0.0733 - val_loss: 0.0837 - val_sparse_categorical_crossentropy: 0.0292 - val_sparse_categorical_accuracy: 0.9895 - val_scaled_adversarial_loss: 0.0545\n",
      "Epoch 728/1000\n",
      "12/12 [==============================] - 6s 475ms/step - loss: 0.1055 - sparse_categorical_crossentropy: 0.0375 - sparse_categorical_accuracy: 0.9865 - scaled_adversarial_loss: 0.0680 - val_loss: 0.0843 - val_sparse_categorical_crossentropy: 0.0309 - val_sparse_categorical_accuracy: 0.9930 - val_scaled_adversarial_loss: 0.0534\n",
      "Epoch 729/1000\n",
      "12/12 [==============================] - 5s 386ms/step - loss: 0.1144 - sparse_categorical_crossentropy: 0.0369 - sparse_categorical_accuracy: 0.9869 - scaled_adversarial_loss: 0.0775 - val_loss: 0.0834 - val_sparse_categorical_crossentropy: 0.0338 - val_sparse_categorical_accuracy: 0.9888 - val_scaled_adversarial_loss: 0.0496\n",
      "Epoch 730/1000\n",
      "12/12 [==============================] - 5s 391ms/step - loss: 0.1147 - sparse_categorical_crossentropy: 0.0374 - sparse_categorical_accuracy: 0.9864 - scaled_adversarial_loss: 0.0774 - val_loss: 0.0926 - val_sparse_categorical_crossentropy: 0.0519 - val_sparse_categorical_accuracy: 0.9860 - val_scaled_adversarial_loss: 0.0407\n",
      "Epoch 731/1000\n",
      "12/12 [==============================] - 4s 360ms/step - loss: 0.1112 - sparse_categorical_crossentropy: 0.0358 - sparse_categorical_accuracy: 0.9864 - scaled_adversarial_loss: 0.0755 - val_loss: 0.0748 - val_sparse_categorical_crossentropy: 0.0343 - val_sparse_categorical_accuracy: 0.9916 - val_scaled_adversarial_loss: 0.0405\n",
      "Epoch 732/1000\n",
      "12/12 [==============================] - 4s 367ms/step - loss: 0.1076 - sparse_categorical_crossentropy: 0.0303 - sparse_categorical_accuracy: 0.9888 - scaled_adversarial_loss: 0.0773 - val_loss: 0.0883 - val_sparse_categorical_crossentropy: 0.0317 - val_sparse_categorical_accuracy: 0.9902 - val_scaled_adversarial_loss: 0.0566\n",
      "Epoch 733/1000\n",
      "12/12 [==============================] - 5s 383ms/step - loss: 0.1016 - sparse_categorical_crossentropy: 0.0272 - sparse_categorical_accuracy: 0.9904 - scaled_adversarial_loss: 0.0744 - val_loss: 0.0801 - val_sparse_categorical_crossentropy: 0.0358 - val_sparse_categorical_accuracy: 0.9916 - val_scaled_adversarial_loss: 0.0442\n",
      "Epoch 734/1000\n",
      "12/12 [==============================] - 5s 397ms/step - loss: 0.1079 - sparse_categorical_crossentropy: 0.0303 - sparse_categorical_accuracy: 0.9892 - scaled_adversarial_loss: 0.0775 - val_loss: 0.0794 - val_sparse_categorical_crossentropy: 0.0307 - val_sparse_categorical_accuracy: 0.9909 - val_scaled_adversarial_loss: 0.0487\n",
      "Epoch 735/1000\n",
      "12/12 [==============================] - 4s 358ms/step - loss: 0.1065 - sparse_categorical_crossentropy: 0.0329 - sparse_categorical_accuracy: 0.9885 - scaled_adversarial_loss: 0.0735 - val_loss: 0.0793 - val_sparse_categorical_crossentropy: 0.0266 - val_sparse_categorical_accuracy: 0.9916 - val_scaled_adversarial_loss: 0.0526\n",
      "Epoch 736/1000\n",
      "12/12 [==============================] - 4s 373ms/step - loss: 0.1007 - sparse_categorical_crossentropy: 0.0286 - sparse_categorical_accuracy: 0.9909 - scaled_adversarial_loss: 0.0720 - val_loss: 0.0723 - val_sparse_categorical_crossentropy: 0.0306 - val_sparse_categorical_accuracy: 0.9895 - val_scaled_adversarial_loss: 0.0418\n",
      "Epoch 737/1000\n",
      "12/12 [==============================] - 4s 370ms/step - loss: 0.1023 - sparse_categorical_crossentropy: 0.0314 - sparse_categorical_accuracy: 0.9899 - scaled_adversarial_loss: 0.0708 - val_loss: 0.0797 - val_sparse_categorical_crossentropy: 0.0354 - val_sparse_categorical_accuracy: 0.9874 - val_scaled_adversarial_loss: 0.0442\n",
      "Epoch 738/1000\n",
      "12/12 [==============================] - 4s 359ms/step - loss: 0.1129 - sparse_categorical_crossentropy: 0.0428 - sparse_categorical_accuracy: 0.9839 - scaled_adversarial_loss: 0.0701 - val_loss: 0.0824 - val_sparse_categorical_crossentropy: 0.0342 - val_sparse_categorical_accuracy: 0.9895 - val_scaled_adversarial_loss: 0.0483\n",
      "Epoch 739/1000\n",
      "12/12 [==============================] - 4s 368ms/step - loss: 0.1121 - sparse_categorical_crossentropy: 0.0343 - sparse_categorical_accuracy: 0.9895 - scaled_adversarial_loss: 0.0778 - val_loss: 0.0871 - val_sparse_categorical_crossentropy: 0.0318 - val_sparse_categorical_accuracy: 0.9909 - val_scaled_adversarial_loss: 0.0553\n",
      "Epoch 740/1000\n",
      "12/12 [==============================] - 4s 365ms/step - loss: 0.1074 - sparse_categorical_crossentropy: 0.0345 - sparse_categorical_accuracy: 0.9878 - scaled_adversarial_loss: 0.0730 - val_loss: 0.0920 - val_sparse_categorical_crossentropy: 0.0423 - val_sparse_categorical_accuracy: 0.9902 - val_scaled_adversarial_loss: 0.0497\n",
      "Epoch 741/1000\n",
      "12/12 [==============================] - 5s 411ms/step - loss: 0.1230 - sparse_categorical_crossentropy: 0.0457 - sparse_categorical_accuracy: 0.9874 - scaled_adversarial_loss: 0.0774 - val_loss: 0.0825 - val_sparse_categorical_crossentropy: 0.0388 - val_sparse_categorical_accuracy: 0.9881 - val_scaled_adversarial_loss: 0.0437\n",
      "Epoch 742/1000\n",
      "12/12 [==============================] - 4s 372ms/step - loss: 0.1079 - sparse_categorical_crossentropy: 0.0358 - sparse_categorical_accuracy: 0.9888 - scaled_adversarial_loss: 0.0720 - val_loss: 0.0829 - val_sparse_categorical_crossentropy: 0.0402 - val_sparse_categorical_accuracy: 0.9860 - val_scaled_adversarial_loss: 0.0427\n",
      "Epoch 743/1000\n",
      "12/12 [==============================] - 4s 373ms/step - loss: 0.1200 - sparse_categorical_crossentropy: 0.0439 - sparse_categorical_accuracy: 0.9848 - scaled_adversarial_loss: 0.0761 - val_loss: 0.0915 - val_sparse_categorical_crossentropy: 0.0350 - val_sparse_categorical_accuracy: 0.9874 - val_scaled_adversarial_loss: 0.0565\n",
      "Epoch 744/1000\n",
      "12/12 [==============================] - 5s 419ms/step - loss: 0.1151 - sparse_categorical_crossentropy: 0.0393 - sparse_categorical_accuracy: 0.9897 - scaled_adversarial_loss: 0.0758 - val_loss: 0.0934 - val_sparse_categorical_crossentropy: 0.0317 - val_sparse_categorical_accuracy: 0.9895 - val_scaled_adversarial_loss: 0.0616\n",
      "Epoch 745/1000\n",
      "12/12 [==============================] - 5s 393ms/step - loss: 0.1107 - sparse_categorical_crossentropy: 0.0375 - sparse_categorical_accuracy: 0.9886 - scaled_adversarial_loss: 0.0732 - val_loss: 0.0828 - val_sparse_categorical_crossentropy: 0.0293 - val_sparse_categorical_accuracy: 0.9909 - val_scaled_adversarial_loss: 0.0534\n",
      "Epoch 746/1000\n",
      "12/12 [==============================] - 5s 394ms/step - loss: 0.1131 - sparse_categorical_crossentropy: 0.0399 - sparse_categorical_accuracy: 0.9881 - scaled_adversarial_loss: 0.0733 - val_loss: 0.0812 - val_sparse_categorical_crossentropy: 0.0337 - val_sparse_categorical_accuracy: 0.9888 - val_scaled_adversarial_loss: 0.0475\n",
      "Epoch 747/1000\n",
      "12/12 [==============================] - 5s 383ms/step - loss: 0.1080 - sparse_categorical_crossentropy: 0.0345 - sparse_categorical_accuracy: 0.9883 - scaled_adversarial_loss: 0.0735 - val_loss: 0.0885 - val_sparse_categorical_crossentropy: 0.0354 - val_sparse_categorical_accuracy: 0.9881 - val_scaled_adversarial_loss: 0.0531\n",
      "Epoch 748/1000\n",
      "12/12 [==============================] - 5s 379ms/step - loss: 0.1087 - sparse_categorical_crossentropy: 0.0293 - sparse_categorical_accuracy: 0.9879 - scaled_adversarial_loss: 0.0794 - val_loss: 0.0918 - val_sparse_categorical_crossentropy: 0.0318 - val_sparse_categorical_accuracy: 0.9909 - val_scaled_adversarial_loss: 0.0599\n",
      "Epoch 749/1000\n",
      "12/12 [==============================] - 5s 409ms/step - loss: 0.1168 - sparse_categorical_crossentropy: 0.0404 - sparse_categorical_accuracy: 0.9895 - scaled_adversarial_loss: 0.0764 - val_loss: 0.0757 - val_sparse_categorical_crossentropy: 0.0298 - val_sparse_categorical_accuracy: 0.9902 - val_scaled_adversarial_loss: 0.0459\n",
      "Epoch 750/1000\n",
      "12/12 [==============================] - 5s 408ms/step - loss: 0.1027 - sparse_categorical_crossentropy: 0.0324 - sparse_categorical_accuracy: 0.9872 - scaled_adversarial_loss: 0.0703 - val_loss: 0.0892 - val_sparse_categorical_crossentropy: 0.0406 - val_sparse_categorical_accuracy: 0.9867 - val_scaled_adversarial_loss: 0.0486\n",
      "Epoch 751/1000\n",
      "12/12 [==============================] - 5s 410ms/step - loss: 0.0973 - sparse_categorical_crossentropy: 0.0261 - sparse_categorical_accuracy: 0.9904 - scaled_adversarial_loss: 0.0712 - val_loss: 0.0869 - val_sparse_categorical_crossentropy: 0.0335 - val_sparse_categorical_accuracy: 0.9895 - val_scaled_adversarial_loss: 0.0534\n",
      "Epoch 752/1000\n",
      "12/12 [==============================] - 5s 393ms/step - loss: 0.1008 - sparse_categorical_crossentropy: 0.0262 - sparse_categorical_accuracy: 0.9902 - scaled_adversarial_loss: 0.0746 - val_loss: 0.0761 - val_sparse_categorical_crossentropy: 0.0313 - val_sparse_categorical_accuracy: 0.9923 - val_scaled_adversarial_loss: 0.0447\n",
      "Epoch 753/1000\n",
      "12/12 [==============================] - 5s 398ms/step - loss: 0.0954 - sparse_categorical_crossentropy: 0.0250 - sparse_categorical_accuracy: 0.9918 - scaled_adversarial_loss: 0.0704 - val_loss: 0.0722 - val_sparse_categorical_crossentropy: 0.0309 - val_sparse_categorical_accuracy: 0.9937 - val_scaled_adversarial_loss: 0.0412\n",
      "Epoch 754/1000\n",
      "12/12 [==============================] - 5s 411ms/step - loss: 0.1004 - sparse_categorical_crossentropy: 0.0281 - sparse_categorical_accuracy: 0.9906 - scaled_adversarial_loss: 0.0723 - val_loss: 0.0706 - val_sparse_categorical_crossentropy: 0.0299 - val_sparse_categorical_accuracy: 0.9923 - val_scaled_adversarial_loss: 0.0407\n",
      "Epoch 755/1000\n",
      "12/12 [==============================] - 5s 405ms/step - loss: 0.0952 - sparse_categorical_crossentropy: 0.0245 - sparse_categorical_accuracy: 0.9920 - scaled_adversarial_loss: 0.0707 - val_loss: 0.0806 - val_sparse_categorical_crossentropy: 0.0279 - val_sparse_categorical_accuracy: 0.9916 - val_scaled_adversarial_loss: 0.0527\n",
      "Epoch 756/1000\n",
      "12/12 [==============================] - 5s 382ms/step - loss: 0.0912 - sparse_categorical_crossentropy: 0.0248 - sparse_categorical_accuracy: 0.9916 - scaled_adversarial_loss: 0.0663 - val_loss: 0.0754 - val_sparse_categorical_crossentropy: 0.0293 - val_sparse_categorical_accuracy: 0.9916 - val_scaled_adversarial_loss: 0.0461\n",
      "Epoch 757/1000\n",
      "12/12 [==============================] - 5s 385ms/step - loss: 0.0986 - sparse_categorical_crossentropy: 0.0279 - sparse_categorical_accuracy: 0.9909 - scaled_adversarial_loss: 0.0707 - val_loss: 0.0785 - val_sparse_categorical_crossentropy: 0.0358 - val_sparse_categorical_accuracy: 0.9888 - val_scaled_adversarial_loss: 0.0427\n",
      "Epoch 758/1000\n",
      "12/12 [==============================] - 5s 386ms/step - loss: 0.0988 - sparse_categorical_crossentropy: 0.0278 - sparse_categorical_accuracy: 0.9911 - scaled_adversarial_loss: 0.0710 - val_loss: 0.0808 - val_sparse_categorical_crossentropy: 0.0285 - val_sparse_categorical_accuracy: 0.9923 - val_scaled_adversarial_loss: 0.0524\n",
      "Epoch 759/1000\n",
      "12/12 [==============================] - 5s 398ms/step - loss: 0.0940 - sparse_categorical_crossentropy: 0.0266 - sparse_categorical_accuracy: 0.9890 - scaled_adversarial_loss: 0.0675 - val_loss: 0.0718 - val_sparse_categorical_crossentropy: 0.0309 - val_sparse_categorical_accuracy: 0.9916 - val_scaled_adversarial_loss: 0.0409\n",
      "Epoch 760/1000\n",
      "12/12 [==============================] - 5s 386ms/step - loss: 0.0943 - sparse_categorical_crossentropy: 0.0261 - sparse_categorical_accuracy: 0.9909 - scaled_adversarial_loss: 0.0682 - val_loss: 0.0708 - val_sparse_categorical_crossentropy: 0.0286 - val_sparse_categorical_accuracy: 0.9916 - val_scaled_adversarial_loss: 0.0422\n",
      "Epoch 761/1000\n",
      "12/12 [==============================] - 5s 385ms/step - loss: 0.0886 - sparse_categorical_crossentropy: 0.0233 - sparse_categorical_accuracy: 0.9925 - scaled_adversarial_loss: 0.0652 - val_loss: 0.0733 - val_sparse_categorical_crossentropy: 0.0293 - val_sparse_categorical_accuracy: 0.9916 - val_scaled_adversarial_loss: 0.0440\n",
      "Epoch 762/1000\n",
      "12/12 [==============================] - 5s 395ms/step - loss: 0.0960 - sparse_categorical_crossentropy: 0.0277 - sparse_categorical_accuracy: 0.9916 - scaled_adversarial_loss: 0.0682 - val_loss: 0.0821 - val_sparse_categorical_crossentropy: 0.0291 - val_sparse_categorical_accuracy: 0.9923 - val_scaled_adversarial_loss: 0.0530\n",
      "Epoch 763/1000\n",
      "12/12 [==============================] - 5s 407ms/step - loss: 0.1044 - sparse_categorical_crossentropy: 0.0326 - sparse_categorical_accuracy: 0.9872 - scaled_adversarial_loss: 0.0717 - val_loss: 0.0964 - val_sparse_categorical_crossentropy: 0.0301 - val_sparse_categorical_accuracy: 0.9937 - val_scaled_adversarial_loss: 0.0664\n",
      "Epoch 764/1000\n",
      "12/12 [==============================] - 5s 398ms/step - loss: 0.1031 - sparse_categorical_crossentropy: 0.0272 - sparse_categorical_accuracy: 0.9906 - scaled_adversarial_loss: 0.0760 - val_loss: 0.0763 - val_sparse_categorical_crossentropy: 0.0263 - val_sparse_categorical_accuracy: 0.9916 - val_scaled_adversarial_loss: 0.0500\n",
      "Epoch 765/1000\n",
      "12/12 [==============================] - 5s 388ms/step - loss: 0.1054 - sparse_categorical_crossentropy: 0.0315 - sparse_categorical_accuracy: 0.9890 - scaled_adversarial_loss: 0.0739 - val_loss: 0.0863 - val_sparse_categorical_crossentropy: 0.0400 - val_sparse_categorical_accuracy: 0.9902 - val_scaled_adversarial_loss: 0.0462\n",
      "Epoch 766/1000\n",
      "12/12 [==============================] - 5s 391ms/step - loss: 0.0980 - sparse_categorical_crossentropy: 0.0259 - sparse_categorical_accuracy: 0.9904 - scaled_adversarial_loss: 0.0721 - val_loss: 0.0762 - val_sparse_categorical_crossentropy: 0.0308 - val_sparse_categorical_accuracy: 0.9930 - val_scaled_adversarial_loss: 0.0454\n",
      "Epoch 767/1000\n",
      "12/12 [==============================] - 5s 397ms/step - loss: 0.1076 - sparse_categorical_crossentropy: 0.0324 - sparse_categorical_accuracy: 0.9890 - scaled_adversarial_loss: 0.0752 - val_loss: 0.0962 - val_sparse_categorical_crossentropy: 0.0451 - val_sparse_categorical_accuracy: 0.9860 - val_scaled_adversarial_loss: 0.0511\n",
      "Epoch 768/1000\n",
      "12/12 [==============================] - 5s 390ms/step - loss: 0.1120 - sparse_categorical_crossentropy: 0.0314 - sparse_categorical_accuracy: 0.9904 - scaled_adversarial_loss: 0.0806 - val_loss: 0.0743 - val_sparse_categorical_crossentropy: 0.0260 - val_sparse_categorical_accuracy: 0.9937 - val_scaled_adversarial_loss: 0.0483\n",
      "Epoch 769/1000\n",
      "12/12 [==============================] - 5s 420ms/step - loss: 0.1086 - sparse_categorical_crossentropy: 0.0330 - sparse_categorical_accuracy: 0.9886 - scaled_adversarial_loss: 0.0756 - val_loss: 0.0749 - val_sparse_categorical_crossentropy: 0.0317 - val_sparse_categorical_accuracy: 0.9916 - val_scaled_adversarial_loss: 0.0432\n",
      "Epoch 770/1000\n",
      "12/12 [==============================] - 5s 396ms/step - loss: 0.1017 - sparse_categorical_crossentropy: 0.0299 - sparse_categorical_accuracy: 0.9888 - scaled_adversarial_loss: 0.0717 - val_loss: 0.0784 - val_sparse_categorical_crossentropy: 0.0269 - val_sparse_categorical_accuracy: 0.9909 - val_scaled_adversarial_loss: 0.0515\n",
      "Epoch 771/1000\n",
      "12/12 [==============================] - 5s 394ms/step - loss: 0.1026 - sparse_categorical_crossentropy: 0.0319 - sparse_categorical_accuracy: 0.9895 - scaled_adversarial_loss: 0.0707 - val_loss: 0.0880 - val_sparse_categorical_crossentropy: 0.0346 - val_sparse_categorical_accuracy: 0.9895 - val_scaled_adversarial_loss: 0.0534\n",
      "Epoch 772/1000\n",
      "12/12 [==============================] - 5s 416ms/step - loss: 0.1071 - sparse_categorical_crossentropy: 0.0352 - sparse_categorical_accuracy: 0.9869 - scaled_adversarial_loss: 0.0719 - val_loss: 0.1073 - val_sparse_categorical_crossentropy: 0.0541 - val_sparse_categorical_accuracy: 0.9804 - val_scaled_adversarial_loss: 0.0532\n",
      "Epoch 773/1000\n",
      "12/12 [==============================] - 5s 398ms/step - loss: 0.1107 - sparse_categorical_crossentropy: 0.0375 - sparse_categorical_accuracy: 0.9864 - scaled_adversarial_loss: 0.0732 - val_loss: 0.0845 - val_sparse_categorical_crossentropy: 0.0317 - val_sparse_categorical_accuracy: 0.9895 - val_scaled_adversarial_loss: 0.0528\n",
      "Epoch 774/1000\n",
      "12/12 [==============================] - 5s 435ms/step - loss: 0.1021 - sparse_categorical_crossentropy: 0.0279 - sparse_categorical_accuracy: 0.9904 - scaled_adversarial_loss: 0.0742 - val_loss: 0.0815 - val_sparse_categorical_crossentropy: 0.0292 - val_sparse_categorical_accuracy: 0.9902 - val_scaled_adversarial_loss: 0.0523\n",
      "Epoch 775/1000\n",
      "12/12 [==============================] - 5s 423ms/step - loss: 0.0970 - sparse_categorical_crossentropy: 0.0300 - sparse_categorical_accuracy: 0.9906 - scaled_adversarial_loss: 0.0670 - val_loss: 0.0836 - val_sparse_categorical_crossentropy: 0.0266 - val_sparse_categorical_accuracy: 0.9923 - val_scaled_adversarial_loss: 0.0570\n",
      "Epoch 776/1000\n",
      "12/12 [==============================] - 5s 432ms/step - loss: 0.0996 - sparse_categorical_crossentropy: 0.0318 - sparse_categorical_accuracy: 0.9893 - scaled_adversarial_loss: 0.0678 - val_loss: 0.0749 - val_sparse_categorical_crossentropy: 0.0318 - val_sparse_categorical_accuracy: 0.9902 - val_scaled_adversarial_loss: 0.0431\n",
      "Epoch 777/1000\n",
      "12/12 [==============================] - 5s 427ms/step - loss: 0.1188 - sparse_categorical_crossentropy: 0.0465 - sparse_categorical_accuracy: 0.9855 - scaled_adversarial_loss: 0.0723 - val_loss: 0.0826 - val_sparse_categorical_crossentropy: 0.0335 - val_sparse_categorical_accuracy: 0.9902 - val_scaled_adversarial_loss: 0.0491\n",
      "Epoch 778/1000\n",
      "12/12 [==============================] - 5s 415ms/step - loss: 0.1144 - sparse_categorical_crossentropy: 0.0370 - sparse_categorical_accuracy: 0.9860 - scaled_adversarial_loss: 0.0773 - val_loss: 0.0897 - val_sparse_categorical_crossentropy: 0.0333 - val_sparse_categorical_accuracy: 0.9881 - val_scaled_adversarial_loss: 0.0563\n",
      "Epoch 779/1000\n",
      "12/12 [==============================] - 5s 412ms/step - loss: 0.1088 - sparse_categorical_crossentropy: 0.0356 - sparse_categorical_accuracy: 0.9860 - scaled_adversarial_loss: 0.0732 - val_loss: 0.0804 - val_sparse_categorical_crossentropy: 0.0345 - val_sparse_categorical_accuracy: 0.9881 - val_scaled_adversarial_loss: 0.0459\n",
      "Epoch 780/1000\n",
      "12/12 [==============================] - 5s 432ms/step - loss: 0.0962 - sparse_categorical_crossentropy: 0.0251 - sparse_categorical_accuracy: 0.9911 - scaled_adversarial_loss: 0.0711 - val_loss: 0.0775 - val_sparse_categorical_crossentropy: 0.0348 - val_sparse_categorical_accuracy: 0.9895 - val_scaled_adversarial_loss: 0.0428\n",
      "Epoch 781/1000\n",
      "12/12 [==============================] - 5s 434ms/step - loss: 0.1014 - sparse_categorical_crossentropy: 0.0333 - sparse_categorical_accuracy: 0.9888 - scaled_adversarial_loss: 0.0680 - val_loss: 0.0746 - val_sparse_categorical_crossentropy: 0.0255 - val_sparse_categorical_accuracy: 0.9923 - val_scaled_adversarial_loss: 0.0491\n",
      "Epoch 782/1000\n",
      "12/12 [==============================] - 5s 416ms/step - loss: 0.1045 - sparse_categorical_crossentropy: 0.0323 - sparse_categorical_accuracy: 0.9881 - scaled_adversarial_loss: 0.0722 - val_loss: 0.0831 - val_sparse_categorical_crossentropy: 0.0366 - val_sparse_categorical_accuracy: 0.9902 - val_scaled_adversarial_loss: 0.0465\n",
      "Epoch 783/1000\n",
      "12/12 [==============================] - 5s 420ms/step - loss: 0.0995 - sparse_categorical_crossentropy: 0.0273 - sparse_categorical_accuracy: 0.9897 - scaled_adversarial_loss: 0.0722 - val_loss: 0.0859 - val_sparse_categorical_crossentropy: 0.0308 - val_sparse_categorical_accuracy: 0.9930 - val_scaled_adversarial_loss: 0.0551\n",
      "Epoch 784/1000\n",
      "12/12 [==============================] - 6s 463ms/step - loss: 0.1013 - sparse_categorical_crossentropy: 0.0268 - sparse_categorical_accuracy: 0.9900 - scaled_adversarial_loss: 0.0746 - val_loss: 0.0731 - val_sparse_categorical_crossentropy: 0.0301 - val_sparse_categorical_accuracy: 0.9937 - val_scaled_adversarial_loss: 0.0430\n",
      "Epoch 785/1000\n",
      "12/12 [==============================] - 6s 494ms/step - loss: 0.0999 - sparse_categorical_crossentropy: 0.0309 - sparse_categorical_accuracy: 0.9881 - scaled_adversarial_loss: 0.0690 - val_loss: 0.0778 - val_sparse_categorical_crossentropy: 0.0351 - val_sparse_categorical_accuracy: 0.9923 - val_scaled_adversarial_loss: 0.0427\n",
      "Epoch 786/1000\n",
      "12/12 [==============================] - 6s 495ms/step - loss: 0.0977 - sparse_categorical_crossentropy: 0.0265 - sparse_categorical_accuracy: 0.9927 - scaled_adversarial_loss: 0.0712 - val_loss: 0.0733 - val_sparse_categorical_crossentropy: 0.0314 - val_sparse_categorical_accuracy: 0.9923 - val_scaled_adversarial_loss: 0.0419\n",
      "Epoch 787/1000\n",
      "12/12 [==============================] - 6s 495ms/step - loss: 0.0984 - sparse_categorical_crossentropy: 0.0319 - sparse_categorical_accuracy: 0.9888 - scaled_adversarial_loss: 0.0665 - val_loss: 0.0832 - val_sparse_categorical_crossentropy: 0.0339 - val_sparse_categorical_accuracy: 0.9930 - val_scaled_adversarial_loss: 0.0494\n",
      "Epoch 788/1000\n",
      "12/12 [==============================] - 6s 501ms/step - loss: 0.1141 - sparse_categorical_crossentropy: 0.0359 - sparse_categorical_accuracy: 0.9906 - scaled_adversarial_loss: 0.0782 - val_loss: 0.0794 - val_sparse_categorical_crossentropy: 0.0271 - val_sparse_categorical_accuracy: 0.9895 - val_scaled_adversarial_loss: 0.0522\n",
      "Epoch 789/1000\n",
      "12/12 [==============================] - 6s 483ms/step - loss: 0.1031 - sparse_categorical_crossentropy: 0.0268 - sparse_categorical_accuracy: 0.9906 - scaled_adversarial_loss: 0.0762 - val_loss: 0.0788 - val_sparse_categorical_crossentropy: 0.0282 - val_sparse_categorical_accuracy: 0.9916 - val_scaled_adversarial_loss: 0.0506\n",
      "Epoch 790/1000\n",
      "12/12 [==============================] - 6s 532ms/step - loss: 0.1050 - sparse_categorical_crossentropy: 0.0351 - sparse_categorical_accuracy: 0.9857 - scaled_adversarial_loss: 0.0699 - val_loss: 0.0834 - val_sparse_categorical_crossentropy: 0.0303 - val_sparse_categorical_accuracy: 0.9923 - val_scaled_adversarial_loss: 0.0530\n",
      "Epoch 791/1000\n",
      "12/12 [==============================] - 6s 494ms/step - loss: 0.1057 - sparse_categorical_crossentropy: 0.0329 - sparse_categorical_accuracy: 0.9892 - scaled_adversarial_loss: 0.0728 - val_loss: 0.0728 - val_sparse_categorical_crossentropy: 0.0266 - val_sparse_categorical_accuracy: 0.9909 - val_scaled_adversarial_loss: 0.0462\n",
      "Epoch 792/1000\n",
      "12/12 [==============================] - 6s 479ms/step - loss: 0.0969 - sparse_categorical_crossentropy: 0.0267 - sparse_categorical_accuracy: 0.9904 - scaled_adversarial_loss: 0.0702 - val_loss: 0.0752 - val_sparse_categorical_crossentropy: 0.0317 - val_sparse_categorical_accuracy: 0.9916 - val_scaled_adversarial_loss: 0.0435\n",
      "Epoch 793/1000\n",
      "12/12 [==============================] - 6s 464ms/step - loss: 0.0971 - sparse_categorical_crossentropy: 0.0274 - sparse_categorical_accuracy: 0.9895 - scaled_adversarial_loss: 0.0697 - val_loss: 0.0784 - val_sparse_categorical_crossentropy: 0.0318 - val_sparse_categorical_accuracy: 0.9916 - val_scaled_adversarial_loss: 0.0466\n",
      "Epoch 794/1000\n",
      "12/12 [==============================] - 6s 476ms/step - loss: 0.1015 - sparse_categorical_crossentropy: 0.0259 - sparse_categorical_accuracy: 0.9907 - scaled_adversarial_loss: 0.0755 - val_loss: 0.0797 - val_sparse_categorical_crossentropy: 0.0297 - val_sparse_categorical_accuracy: 0.9909 - val_scaled_adversarial_loss: 0.0500\n",
      "Epoch 795/1000\n",
      "12/12 [==============================] - 6s 479ms/step - loss: 0.0982 - sparse_categorical_crossentropy: 0.0278 - sparse_categorical_accuracy: 0.9909 - scaled_adversarial_loss: 0.0704 - val_loss: 0.0769 - val_sparse_categorical_crossentropy: 0.0306 - val_sparse_categorical_accuracy: 0.9937 - val_scaled_adversarial_loss: 0.0463\n",
      "Epoch 796/1000\n",
      "12/12 [==============================] - 6s 493ms/step - loss: 0.0951 - sparse_categorical_crossentropy: 0.0233 - sparse_categorical_accuracy: 0.9927 - scaled_adversarial_loss: 0.0718 - val_loss: 0.0796 - val_sparse_categorical_crossentropy: 0.0334 - val_sparse_categorical_accuracy: 0.9923 - val_scaled_adversarial_loss: 0.0462\n",
      "Epoch 797/1000\n",
      "12/12 [==============================] - 6s 485ms/step - loss: 0.0960 - sparse_categorical_crossentropy: 0.0248 - sparse_categorical_accuracy: 0.9918 - scaled_adversarial_loss: 0.0712 - val_loss: 0.0752 - val_sparse_categorical_crossentropy: 0.0303 - val_sparse_categorical_accuracy: 0.9923 - val_scaled_adversarial_loss: 0.0448\n",
      "Epoch 798/1000\n",
      "12/12 [==============================] - 6s 484ms/step - loss: 0.0967 - sparse_categorical_crossentropy: 0.0273 - sparse_categorical_accuracy: 0.9909 - scaled_adversarial_loss: 0.0694 - val_loss: 0.0755 - val_sparse_categorical_crossentropy: 0.0275 - val_sparse_categorical_accuracy: 0.9916 - val_scaled_adversarial_loss: 0.0480\n",
      "Epoch 799/1000\n",
      "12/12 [==============================] - 6s 514ms/step - loss: 0.0992 - sparse_categorical_crossentropy: 0.0265 - sparse_categorical_accuracy: 0.9914 - scaled_adversarial_loss: 0.0728 - val_loss: 0.0761 - val_sparse_categorical_crossentropy: 0.0273 - val_sparse_categorical_accuracy: 0.9909 - val_scaled_adversarial_loss: 0.0488\n",
      "Epoch 800/1000\n",
      "12/12 [==============================] - 6s 486ms/step - loss: 0.1017 - sparse_categorical_crossentropy: 0.0274 - sparse_categorical_accuracy: 0.9904 - scaled_adversarial_loss: 0.0743 - val_loss: 0.0847 - val_sparse_categorical_crossentropy: 0.0288 - val_sparse_categorical_accuracy: 0.9909 - val_scaled_adversarial_loss: 0.0560\n",
      "Epoch 801/1000\n",
      "12/12 [==============================] - 6s 477ms/step - loss: 0.0964 - sparse_categorical_crossentropy: 0.0267 - sparse_categorical_accuracy: 0.9913 - scaled_adversarial_loss: 0.0696 - val_loss: 0.0803 - val_sparse_categorical_crossentropy: 0.0279 - val_sparse_categorical_accuracy: 0.9902 - val_scaled_adversarial_loss: 0.0525\n",
      "Epoch 802/1000\n",
      "12/12 [==============================] - 6s 475ms/step - loss: 0.1031 - sparse_categorical_crossentropy: 0.0295 - sparse_categorical_accuracy: 0.9925 - scaled_adversarial_loss: 0.0737 - val_loss: 0.0767 - val_sparse_categorical_crossentropy: 0.0330 - val_sparse_categorical_accuracy: 0.9930 - val_scaled_adversarial_loss: 0.0437\n",
      "Epoch 803/1000\n",
      "12/12 [==============================] - 6s 495ms/step - loss: 0.1054 - sparse_categorical_crossentropy: 0.0342 - sparse_categorical_accuracy: 0.9886 - scaled_adversarial_loss: 0.0712 - val_loss: 0.0803 - val_sparse_categorical_crossentropy: 0.0318 - val_sparse_categorical_accuracy: 0.9895 - val_scaled_adversarial_loss: 0.0485\n",
      "Epoch 804/1000\n",
      "12/12 [==============================] - 6s 487ms/step - loss: 0.0960 - sparse_categorical_crossentropy: 0.0231 - sparse_categorical_accuracy: 0.9925 - scaled_adversarial_loss: 0.0729 - val_loss: 0.0823 - val_sparse_categorical_crossentropy: 0.0275 - val_sparse_categorical_accuracy: 0.9930 - val_scaled_adversarial_loss: 0.0548\n",
      "Epoch 805/1000\n",
      "12/12 [==============================] - 6s 492ms/step - loss: 0.0982 - sparse_categorical_crossentropy: 0.0271 - sparse_categorical_accuracy: 0.9921 - scaled_adversarial_loss: 0.0711 - val_loss: 0.0790 - val_sparse_categorical_crossentropy: 0.0244 - val_sparse_categorical_accuracy: 0.9916 - val_scaled_adversarial_loss: 0.0546\n",
      "Epoch 806/1000\n",
      "12/12 [==============================] - 6s 485ms/step - loss: 0.1105 - sparse_categorical_crossentropy: 0.0347 - sparse_categorical_accuracy: 0.9895 - scaled_adversarial_loss: 0.0758 - val_loss: 0.0816 - val_sparse_categorical_crossentropy: 0.0345 - val_sparse_categorical_accuracy: 0.9909 - val_scaled_adversarial_loss: 0.0471\n",
      "Epoch 807/1000\n",
      "12/12 [==============================] - 6s 513ms/step - loss: 0.1181 - sparse_categorical_crossentropy: 0.0407 - sparse_categorical_accuracy: 0.9851 - scaled_adversarial_loss: 0.0774 - val_loss: 0.0861 - val_sparse_categorical_crossentropy: 0.0421 - val_sparse_categorical_accuracy: 0.9888 - val_scaled_adversarial_loss: 0.0440\n",
      "Epoch 808/1000\n",
      "12/12 [==============================] - 6s 514ms/step - loss: 0.1025 - sparse_categorical_crossentropy: 0.0327 - sparse_categorical_accuracy: 0.9890 - scaled_adversarial_loss: 0.0698 - val_loss: 0.0793 - val_sparse_categorical_crossentropy: 0.0318 - val_sparse_categorical_accuracy: 0.9916 - val_scaled_adversarial_loss: 0.0475\n",
      "Epoch 809/1000\n",
      "12/12 [==============================] - 6s 530ms/step - loss: 0.1025 - sparse_categorical_crossentropy: 0.0285 - sparse_categorical_accuracy: 0.9911 - scaled_adversarial_loss: 0.0740 - val_loss: 0.0835 - val_sparse_categorical_crossentropy: 0.0372 - val_sparse_categorical_accuracy: 0.9874 - val_scaled_adversarial_loss: 0.0462\n",
      "Epoch 810/1000\n",
      "12/12 [==============================] - 6s 507ms/step - loss: 0.1055 - sparse_categorical_crossentropy: 0.0307 - sparse_categorical_accuracy: 0.9888 - scaled_adversarial_loss: 0.0748 - val_loss: 0.0950 - val_sparse_categorical_crossentropy: 0.0488 - val_sparse_categorical_accuracy: 0.9881 - val_scaled_adversarial_loss: 0.0462\n",
      "Epoch 811/1000\n",
      "12/12 [==============================] - 6s 532ms/step - loss: 0.1045 - sparse_categorical_crossentropy: 0.0317 - sparse_categorical_accuracy: 0.9895 - scaled_adversarial_loss: 0.0728 - val_loss: 0.0840 - val_sparse_categorical_crossentropy: 0.0373 - val_sparse_categorical_accuracy: 0.9874 - val_scaled_adversarial_loss: 0.0466\n",
      "Epoch 812/1000\n",
      "12/12 [==============================] - 6s 477ms/step - loss: 0.0966 - sparse_categorical_crossentropy: 0.0263 - sparse_categorical_accuracy: 0.9921 - scaled_adversarial_loss: 0.0703 - val_loss: 0.0884 - val_sparse_categorical_crossentropy: 0.0453 - val_sparse_categorical_accuracy: 0.9888 - val_scaled_adversarial_loss: 0.0431\n",
      "Epoch 813/1000\n",
      "12/12 [==============================] - 6s 493ms/step - loss: 0.1068 - sparse_categorical_crossentropy: 0.0331 - sparse_categorical_accuracy: 0.9867 - scaled_adversarial_loss: 0.0737 - val_loss: 0.0753 - val_sparse_categorical_crossentropy: 0.0363 - val_sparse_categorical_accuracy: 0.9902 - val_scaled_adversarial_loss: 0.0390\n",
      "Epoch 814/1000\n",
      "12/12 [==============================] - 6s 472ms/step - loss: 0.1004 - sparse_categorical_crossentropy: 0.0286 - sparse_categorical_accuracy: 0.9900 - scaled_adversarial_loss: 0.0718 - val_loss: 0.0807 - val_sparse_categorical_crossentropy: 0.0335 - val_sparse_categorical_accuracy: 0.9895 - val_scaled_adversarial_loss: 0.0472\n",
      "Epoch 815/1000\n",
      "12/12 [==============================] - 6s 476ms/step - loss: 0.0974 - sparse_categorical_crossentropy: 0.0247 - sparse_categorical_accuracy: 0.9925 - scaled_adversarial_loss: 0.0727 - val_loss: 0.0722 - val_sparse_categorical_crossentropy: 0.0327 - val_sparse_categorical_accuracy: 0.9902 - val_scaled_adversarial_loss: 0.0395\n",
      "Epoch 816/1000\n",
      "12/12 [==============================] - 6s 482ms/step - loss: 0.1086 - sparse_categorical_crossentropy: 0.0392 - sparse_categorical_accuracy: 0.9869 - scaled_adversarial_loss: 0.0694 - val_loss: 0.0792 - val_sparse_categorical_crossentropy: 0.0338 - val_sparse_categorical_accuracy: 0.9909 - val_scaled_adversarial_loss: 0.0454\n",
      "Epoch 817/1000\n",
      "12/12 [==============================] - 6s 468ms/step - loss: 0.1061 - sparse_categorical_crossentropy: 0.0333 - sparse_categorical_accuracy: 0.9888 - scaled_adversarial_loss: 0.0727 - val_loss: 0.0876 - val_sparse_categorical_crossentropy: 0.0348 - val_sparse_categorical_accuracy: 0.9881 - val_scaled_adversarial_loss: 0.0528\n",
      "Epoch 818/1000\n",
      "12/12 [==============================] - 6s 514ms/step - loss: 0.0952 - sparse_categorical_crossentropy: 0.0253 - sparse_categorical_accuracy: 0.9909 - scaled_adversarial_loss: 0.0699 - val_loss: 0.0786 - val_sparse_categorical_crossentropy: 0.0306 - val_sparse_categorical_accuracy: 0.9923 - val_scaled_adversarial_loss: 0.0480\n",
      "Epoch 819/1000\n",
      "12/12 [==============================] - 6s 483ms/step - loss: 0.1018 - sparse_categorical_crossentropy: 0.0326 - sparse_categorical_accuracy: 0.9886 - scaled_adversarial_loss: 0.0692 - val_loss: 0.0964 - val_sparse_categorical_crossentropy: 0.0518 - val_sparse_categorical_accuracy: 0.9895 - val_scaled_adversarial_loss: 0.0446\n",
      "Epoch 820/1000\n",
      "12/12 [==============================] - 6s 489ms/step - loss: 0.1056 - sparse_categorical_crossentropy: 0.0357 - sparse_categorical_accuracy: 0.9867 - scaled_adversarial_loss: 0.0700 - val_loss: 0.0826 - val_sparse_categorical_crossentropy: 0.0362 - val_sparse_categorical_accuracy: 0.9916 - val_scaled_adversarial_loss: 0.0463\n",
      "Epoch 821/1000\n",
      "12/12 [==============================] - 6s 502ms/step - loss: 0.1018 - sparse_categorical_crossentropy: 0.0316 - sparse_categorical_accuracy: 0.9890 - scaled_adversarial_loss: 0.0702 - val_loss: 0.0827 - val_sparse_categorical_crossentropy: 0.0328 - val_sparse_categorical_accuracy: 0.9909 - val_scaled_adversarial_loss: 0.0499\n",
      "Epoch 822/1000\n",
      "12/12 [==============================] - 6s 497ms/step - loss: 0.0968 - sparse_categorical_crossentropy: 0.0286 - sparse_categorical_accuracy: 0.9888 - scaled_adversarial_loss: 0.0683 - val_loss: 0.0837 - val_sparse_categorical_crossentropy: 0.0382 - val_sparse_categorical_accuracy: 0.9895 - val_scaled_adversarial_loss: 0.0455\n",
      "Epoch 823/1000\n",
      "12/12 [==============================] - 6s 492ms/step - loss: 0.0976 - sparse_categorical_crossentropy: 0.0288 - sparse_categorical_accuracy: 0.9914 - scaled_adversarial_loss: 0.0688 - val_loss: 0.0886 - val_sparse_categorical_crossentropy: 0.0457 - val_sparse_categorical_accuracy: 0.9881 - val_scaled_adversarial_loss: 0.0429\n",
      "Epoch 824/1000\n",
      "12/12 [==============================] - 6s 505ms/step - loss: 0.1055 - sparse_categorical_crossentropy: 0.0345 - sparse_categorical_accuracy: 0.9899 - scaled_adversarial_loss: 0.0709 - val_loss: 0.0865 - val_sparse_categorical_crossentropy: 0.0422 - val_sparse_categorical_accuracy: 0.9881 - val_scaled_adversarial_loss: 0.0443\n",
      "Epoch 825/1000\n",
      "12/12 [==============================] - 6s 482ms/step - loss: 0.1057 - sparse_categorical_crossentropy: 0.0375 - sparse_categorical_accuracy: 0.9860 - scaled_adversarial_loss: 0.0682 - val_loss: 0.0837 - val_sparse_categorical_crossentropy: 0.0379 - val_sparse_categorical_accuracy: 0.9895 - val_scaled_adversarial_loss: 0.0459\n",
      "Epoch 826/1000\n",
      "12/12 [==============================] - 6s 489ms/step - loss: 0.1053 - sparse_categorical_crossentropy: 0.0325 - sparse_categorical_accuracy: 0.9907 - scaled_adversarial_loss: 0.0728 - val_loss: 0.0916 - val_sparse_categorical_crossentropy: 0.0356 - val_sparse_categorical_accuracy: 0.9881 - val_scaled_adversarial_loss: 0.0561\n",
      "Epoch 827/1000\n",
      "12/12 [==============================] - 6s 482ms/step - loss: 0.1095 - sparse_categorical_crossentropy: 0.0368 - sparse_categorical_accuracy: 0.9865 - scaled_adversarial_loss: 0.0727 - val_loss: 0.0773 - val_sparse_categorical_crossentropy: 0.0313 - val_sparse_categorical_accuracy: 0.9916 - val_scaled_adversarial_loss: 0.0460\n",
      "Epoch 828/1000\n",
      "12/12 [==============================] - 6s 475ms/step - loss: 0.1039 - sparse_categorical_crossentropy: 0.0334 - sparse_categorical_accuracy: 0.9892 - scaled_adversarial_loss: 0.0705 - val_loss: 0.0873 - val_sparse_categorical_crossentropy: 0.0319 - val_sparse_categorical_accuracy: 0.9895 - val_scaled_adversarial_loss: 0.0554\n",
      "Epoch 829/1000\n",
      "12/12 [==============================] - 6s 507ms/step - loss: 0.0925 - sparse_categorical_crossentropy: 0.0226 - sparse_categorical_accuracy: 0.9914 - scaled_adversarial_loss: 0.0700 - val_loss: 0.0717 - val_sparse_categorical_crossentropy: 0.0266 - val_sparse_categorical_accuracy: 0.9930 - val_scaled_adversarial_loss: 0.0451\n",
      "Epoch 830/1000\n",
      "12/12 [==============================] - 7s 555ms/step - loss: 0.0887 - sparse_categorical_crossentropy: 0.0207 - sparse_categorical_accuracy: 0.9925 - scaled_adversarial_loss: 0.0681 - val_loss: 0.0753 - val_sparse_categorical_crossentropy: 0.0323 - val_sparse_categorical_accuracy: 0.9930 - val_scaled_adversarial_loss: 0.0430\n",
      "Epoch 831/1000\n",
      "12/12 [==============================] - 6s 491ms/step - loss: 0.0930 - sparse_categorical_crossentropy: 0.0232 - sparse_categorical_accuracy: 0.9914 - scaled_adversarial_loss: 0.0699 - val_loss: 0.0725 - val_sparse_categorical_crossentropy: 0.0357 - val_sparse_categorical_accuracy: 0.9916 - val_scaled_adversarial_loss: 0.0368\n",
      "Epoch 832/1000\n",
      "12/12 [==============================] - 6s 497ms/step - loss: 0.1006 - sparse_categorical_crossentropy: 0.0265 - sparse_categorical_accuracy: 0.9899 - scaled_adversarial_loss: 0.0740 - val_loss: 0.0767 - val_sparse_categorical_crossentropy: 0.0373 - val_sparse_categorical_accuracy: 0.9895 - val_scaled_adversarial_loss: 0.0394\n",
      "Epoch 833/1000\n",
      "12/12 [==============================] - 6s 474ms/step - loss: 0.1054 - sparse_categorical_crossentropy: 0.0330 - sparse_categorical_accuracy: 0.9900 - scaled_adversarial_loss: 0.0724 - val_loss: 0.0812 - val_sparse_categorical_crossentropy: 0.0406 - val_sparse_categorical_accuracy: 0.9881 - val_scaled_adversarial_loss: 0.0405\n",
      "Epoch 834/1000\n",
      "12/12 [==============================] - 6s 475ms/step - loss: 0.1030 - sparse_categorical_crossentropy: 0.0329 - sparse_categorical_accuracy: 0.9869 - scaled_adversarial_loss: 0.0702 - val_loss: 0.0732 - val_sparse_categorical_crossentropy: 0.0301 - val_sparse_categorical_accuracy: 0.9923 - val_scaled_adversarial_loss: 0.0431\n",
      "Epoch 835/1000\n",
      "12/12 [==============================] - 5s 456ms/step - loss: 0.1105 - sparse_categorical_crossentropy: 0.0378 - sparse_categorical_accuracy: 0.9872 - scaled_adversarial_loss: 0.0727 - val_loss: 0.0884 - val_sparse_categorical_crossentropy: 0.0313 - val_sparse_categorical_accuracy: 0.9923 - val_scaled_adversarial_loss: 0.0571\n",
      "Epoch 836/1000\n",
      "12/12 [==============================] - 6s 481ms/step - loss: 0.1034 - sparse_categorical_crossentropy: 0.0308 - sparse_categorical_accuracy: 0.9899 - scaled_adversarial_loss: 0.0726 - val_loss: 0.0917 - val_sparse_categorical_crossentropy: 0.0407 - val_sparse_categorical_accuracy: 0.9874 - val_scaled_adversarial_loss: 0.0509\n",
      "Epoch 837/1000\n",
      "12/12 [==============================] - 6s 468ms/step - loss: 0.1115 - sparse_categorical_crossentropy: 0.0389 - sparse_categorical_accuracy: 0.9890 - scaled_adversarial_loss: 0.0725 - val_loss: 0.0755 - val_sparse_categorical_crossentropy: 0.0315 - val_sparse_categorical_accuracy: 0.9902 - val_scaled_adversarial_loss: 0.0440\n",
      "Epoch 838/1000\n",
      "12/12 [==============================] - 6s 467ms/step - loss: 0.1053 - sparse_categorical_crossentropy: 0.0350 - sparse_categorical_accuracy: 0.9883 - scaled_adversarial_loss: 0.0703 - val_loss: 0.0689 - val_sparse_categorical_crossentropy: 0.0291 - val_sparse_categorical_accuracy: 0.9916 - val_scaled_adversarial_loss: 0.0398\n",
      "Epoch 839/1000\n",
      "12/12 [==============================] - 6s 464ms/step - loss: 0.0960 - sparse_categorical_crossentropy: 0.0262 - sparse_categorical_accuracy: 0.9906 - scaled_adversarial_loss: 0.0699 - val_loss: 0.0712 - val_sparse_categorical_crossentropy: 0.0277 - val_sparse_categorical_accuracy: 0.9923 - val_scaled_adversarial_loss: 0.0435\n",
      "Epoch 840/1000\n",
      "12/12 [==============================] - 6s 467ms/step - loss: 0.0960 - sparse_categorical_crossentropy: 0.0293 - sparse_categorical_accuracy: 0.9886 - scaled_adversarial_loss: 0.0667 - val_loss: 0.0742 - val_sparse_categorical_crossentropy: 0.0336 - val_sparse_categorical_accuracy: 0.9895 - val_scaled_adversarial_loss: 0.0405\n",
      "Epoch 841/1000\n",
      "12/12 [==============================] - 6s 470ms/step - loss: 0.0988 - sparse_categorical_crossentropy: 0.0273 - sparse_categorical_accuracy: 0.9906 - scaled_adversarial_loss: 0.0714 - val_loss: 0.0735 - val_sparse_categorical_crossentropy: 0.0309 - val_sparse_categorical_accuracy: 0.9916 - val_scaled_adversarial_loss: 0.0426\n",
      "Epoch 842/1000\n",
      "12/12 [==============================] - 6s 466ms/step - loss: 0.0919 - sparse_categorical_crossentropy: 0.0219 - sparse_categorical_accuracy: 0.9927 - scaled_adversarial_loss: 0.0700 - val_loss: 0.0740 - val_sparse_categorical_crossentropy: 0.0352 - val_sparse_categorical_accuracy: 0.9902 - val_scaled_adversarial_loss: 0.0388\n",
      "Epoch 843/1000\n",
      "12/12 [==============================] - 6s 493ms/step - loss: 0.0937 - sparse_categorical_crossentropy: 0.0228 - sparse_categorical_accuracy: 0.9920 - scaled_adversarial_loss: 0.0709 - val_loss: 0.0769 - val_sparse_categorical_crossentropy: 0.0347 - val_sparse_categorical_accuracy: 0.9923 - val_scaled_adversarial_loss: 0.0421\n",
      "Epoch 844/1000\n",
      "12/12 [==============================] - 6s 472ms/step - loss: 0.1009 - sparse_categorical_crossentropy: 0.0275 - sparse_categorical_accuracy: 0.9893 - scaled_adversarial_loss: 0.0735 - val_loss: 0.0786 - val_sparse_categorical_crossentropy: 0.0315 - val_sparse_categorical_accuracy: 0.9916 - val_scaled_adversarial_loss: 0.0471\n",
      "Epoch 845/1000\n",
      "12/12 [==============================] - 6s 468ms/step - loss: 0.0996 - sparse_categorical_crossentropy: 0.0289 - sparse_categorical_accuracy: 0.9918 - scaled_adversarial_loss: 0.0707 - val_loss: 0.1096 - val_sparse_categorical_crossentropy: 0.0312 - val_sparse_categorical_accuracy: 0.9923 - val_scaled_adversarial_loss: 0.0784\n",
      "Epoch 846/1000\n",
      "12/12 [==============================] - 5s 463ms/step - loss: 0.1049 - sparse_categorical_crossentropy: 0.0322 - sparse_categorical_accuracy: 0.9886 - scaled_adversarial_loss: 0.0726 - val_loss: 0.0895 - val_sparse_categorical_crossentropy: 0.0409 - val_sparse_categorical_accuracy: 0.9881 - val_scaled_adversarial_loss: 0.0486\n",
      "Epoch 847/1000\n",
      "12/12 [==============================] - 5s 425ms/step - loss: 0.0947 - sparse_categorical_crossentropy: 0.0229 - sparse_categorical_accuracy: 0.9925 - scaled_adversarial_loss: 0.0717 - val_loss: 0.0882 - val_sparse_categorical_crossentropy: 0.0349 - val_sparse_categorical_accuracy: 0.9916 - val_scaled_adversarial_loss: 0.0533\n",
      "Epoch 848/1000\n",
      "12/12 [==============================] - 5s 390ms/step - loss: 0.0996 - sparse_categorical_crossentropy: 0.0293 - sparse_categorical_accuracy: 0.9900 - scaled_adversarial_loss: 0.0703 - val_loss: 0.0775 - val_sparse_categorical_crossentropy: 0.0308 - val_sparse_categorical_accuracy: 0.9930 - val_scaled_adversarial_loss: 0.0467\n",
      "Epoch 849/1000\n",
      "12/12 [==============================] - 5s 384ms/step - loss: 0.1042 - sparse_categorical_crossentropy: 0.0288 - sparse_categorical_accuracy: 0.9909 - scaled_adversarial_loss: 0.0754 - val_loss: 0.0747 - val_sparse_categorical_crossentropy: 0.0321 - val_sparse_categorical_accuracy: 0.9916 - val_scaled_adversarial_loss: 0.0426\n",
      "Epoch 850/1000\n",
      "12/12 [==============================] - 5s 401ms/step - loss: 0.0985 - sparse_categorical_crossentropy: 0.0305 - sparse_categorical_accuracy: 0.9902 - scaled_adversarial_loss: 0.0680 - val_loss: 0.0739 - val_sparse_categorical_crossentropy: 0.0277 - val_sparse_categorical_accuracy: 0.9930 - val_scaled_adversarial_loss: 0.0462\n",
      "Epoch 851/1000\n",
      "12/12 [==============================] - 5s 384ms/step - loss: 0.0970 - sparse_categorical_crossentropy: 0.0265 - sparse_categorical_accuracy: 0.9900 - scaled_adversarial_loss: 0.0705 - val_loss: 0.0711 - val_sparse_categorical_crossentropy: 0.0293 - val_sparse_categorical_accuracy: 0.9895 - val_scaled_adversarial_loss: 0.0418\n",
      "Epoch 852/1000\n",
      "12/12 [==============================] - 5s 393ms/step - loss: 0.0881 - sparse_categorical_crossentropy: 0.0240 - sparse_categorical_accuracy: 0.9923 - scaled_adversarial_loss: 0.0641 - val_loss: 0.0715 - val_sparse_categorical_crossentropy: 0.0302 - val_sparse_categorical_accuracy: 0.9909 - val_scaled_adversarial_loss: 0.0413\n",
      "Epoch 853/1000\n",
      "12/12 [==============================] - 5s 379ms/step - loss: 0.0883 - sparse_categorical_crossentropy: 0.0199 - sparse_categorical_accuracy: 0.9921 - scaled_adversarial_loss: 0.0683 - val_loss: 0.0782 - val_sparse_categorical_crossentropy: 0.0331 - val_sparse_categorical_accuracy: 0.9916 - val_scaled_adversarial_loss: 0.0451\n",
      "Epoch 854/1000\n",
      "12/12 [==============================] - 4s 376ms/step - loss: 0.0878 - sparse_categorical_crossentropy: 0.0198 - sparse_categorical_accuracy: 0.9930 - scaled_adversarial_loss: 0.0680 - val_loss: 0.0881 - val_sparse_categorical_crossentropy: 0.0372 - val_sparse_categorical_accuracy: 0.9909 - val_scaled_adversarial_loss: 0.0510\n",
      "Epoch 855/1000\n",
      "12/12 [==============================] - 5s 399ms/step - loss: 0.1049 - sparse_categorical_crossentropy: 0.0283 - sparse_categorical_accuracy: 0.9907 - scaled_adversarial_loss: 0.0766 - val_loss: 0.0916 - val_sparse_categorical_crossentropy: 0.0379 - val_sparse_categorical_accuracy: 0.9902 - val_scaled_adversarial_loss: 0.0537\n",
      "Epoch 856/1000\n",
      "12/12 [==============================] - 5s 381ms/step - loss: 0.1007 - sparse_categorical_crossentropy: 0.0303 - sparse_categorical_accuracy: 0.9902 - scaled_adversarial_loss: 0.0704 - val_loss: 0.0929 - val_sparse_categorical_crossentropy: 0.0448 - val_sparse_categorical_accuracy: 0.9874 - val_scaled_adversarial_loss: 0.0480\n",
      "Epoch 857/1000\n",
      "12/12 [==============================] - 5s 383ms/step - loss: 0.1068 - sparse_categorical_crossentropy: 0.0321 - sparse_categorical_accuracy: 0.9897 - scaled_adversarial_loss: 0.0747 - val_loss: 0.0967 - val_sparse_categorical_crossentropy: 0.0345 - val_sparse_categorical_accuracy: 0.9902 - val_scaled_adversarial_loss: 0.0622\n",
      "Epoch 858/1000\n",
      "12/12 [==============================] - 5s 386ms/step - loss: 0.1031 - sparse_categorical_crossentropy: 0.0274 - sparse_categorical_accuracy: 0.9899 - scaled_adversarial_loss: 0.0756 - val_loss: 0.1107 - val_sparse_categorical_crossentropy: 0.0506 - val_sparse_categorical_accuracy: 0.9881 - val_scaled_adversarial_loss: 0.0601\n",
      "Epoch 859/1000\n",
      "12/12 [==============================] - 5s 380ms/step - loss: 0.1063 - sparse_categorical_crossentropy: 0.0322 - sparse_categorical_accuracy: 0.9893 - scaled_adversarial_loss: 0.0741 - val_loss: 0.0909 - val_sparse_categorical_crossentropy: 0.0335 - val_sparse_categorical_accuracy: 0.9895 - val_scaled_adversarial_loss: 0.0573\n",
      "Epoch 860/1000\n",
      "12/12 [==============================] - 5s 383ms/step - loss: 0.1059 - sparse_categorical_crossentropy: 0.0321 - sparse_categorical_accuracy: 0.9897 - scaled_adversarial_loss: 0.0738 - val_loss: 0.0799 - val_sparse_categorical_crossentropy: 0.0286 - val_sparse_categorical_accuracy: 0.9909 - val_scaled_adversarial_loss: 0.0513\n",
      "Epoch 861/1000\n",
      "12/12 [==============================] - 5s 390ms/step - loss: 0.0958 - sparse_categorical_crossentropy: 0.0263 - sparse_categorical_accuracy: 0.9914 - scaled_adversarial_loss: 0.0695 - val_loss: 0.0836 - val_sparse_categorical_crossentropy: 0.0333 - val_sparse_categorical_accuracy: 0.9916 - val_scaled_adversarial_loss: 0.0502\n",
      "Epoch 862/1000\n",
      "12/12 [==============================] - 5s 423ms/step - loss: 0.0964 - sparse_categorical_crossentropy: 0.0233 - sparse_categorical_accuracy: 0.9902 - scaled_adversarial_loss: 0.0731 - val_loss: 0.0770 - val_sparse_categorical_crossentropy: 0.0339 - val_sparse_categorical_accuracy: 0.9902 - val_scaled_adversarial_loss: 0.0431\n",
      "Epoch 863/1000\n",
      "12/12 [==============================] - 5s 388ms/step - loss: 0.0936 - sparse_categorical_crossentropy: 0.0265 - sparse_categorical_accuracy: 0.9906 - scaled_adversarial_loss: 0.0671 - val_loss: 0.0835 - val_sparse_categorical_crossentropy: 0.0376 - val_sparse_categorical_accuracy: 0.9888 - val_scaled_adversarial_loss: 0.0460\n",
      "Epoch 864/1000\n",
      "12/12 [==============================] - 5s 380ms/step - loss: 0.1105 - sparse_categorical_crossentropy: 0.0394 - sparse_categorical_accuracy: 0.9888 - scaled_adversarial_loss: 0.0711 - val_loss: 0.0843 - val_sparse_categorical_crossentropy: 0.0371 - val_sparse_categorical_accuracy: 0.9874 - val_scaled_adversarial_loss: 0.0471\n",
      "Epoch 865/1000\n",
      "12/12 [==============================] - 5s 408ms/step - loss: 0.1075 - sparse_categorical_crossentropy: 0.0338 - sparse_categorical_accuracy: 0.9895 - scaled_adversarial_loss: 0.0736 - val_loss: 0.0817 - val_sparse_categorical_crossentropy: 0.0388 - val_sparse_categorical_accuracy: 0.9888 - val_scaled_adversarial_loss: 0.0430\n",
      "Epoch 866/1000\n",
      "12/12 [==============================] - 5s 395ms/step - loss: 0.0923 - sparse_categorical_crossentropy: 0.0248 - sparse_categorical_accuracy: 0.9916 - scaled_adversarial_loss: 0.0675 - val_loss: 0.0932 - val_sparse_categorical_crossentropy: 0.0433 - val_sparse_categorical_accuracy: 0.9895 - val_scaled_adversarial_loss: 0.0498\n",
      "Epoch 867/1000\n",
      "12/12 [==============================] - 4s 375ms/step - loss: 0.0970 - sparse_categorical_crossentropy: 0.0264 - sparse_categorical_accuracy: 0.9913 - scaled_adversarial_loss: 0.0706 - val_loss: 0.0824 - val_sparse_categorical_crossentropy: 0.0374 - val_sparse_categorical_accuracy: 0.9895 - val_scaled_adversarial_loss: 0.0450\n",
      "Epoch 868/1000\n",
      "12/12 [==============================] - 4s 371ms/step - loss: 0.0970 - sparse_categorical_crossentropy: 0.0275 - sparse_categorical_accuracy: 0.9925 - scaled_adversarial_loss: 0.0696 - val_loss: 0.0786 - val_sparse_categorical_crossentropy: 0.0309 - val_sparse_categorical_accuracy: 0.9923 - val_scaled_adversarial_loss: 0.0477\n",
      "Epoch 869/1000\n",
      "12/12 [==============================] - 4s 373ms/step - loss: 0.0957 - sparse_categorical_crossentropy: 0.0268 - sparse_categorical_accuracy: 0.9886 - scaled_adversarial_loss: 0.0689 - val_loss: 0.0848 - val_sparse_categorical_crossentropy: 0.0339 - val_sparse_categorical_accuracy: 0.9902 - val_scaled_adversarial_loss: 0.0508\n",
      "Epoch 870/1000\n",
      "12/12 [==============================] - 4s 376ms/step - loss: 0.0956 - sparse_categorical_crossentropy: 0.0255 - sparse_categorical_accuracy: 0.9907 - scaled_adversarial_loss: 0.0701 - val_loss: 0.0823 - val_sparse_categorical_crossentropy: 0.0287 - val_sparse_categorical_accuracy: 0.9888 - val_scaled_adversarial_loss: 0.0536\n",
      "Epoch 871/1000\n",
      "12/12 [==============================] - 4s 371ms/step - loss: 0.0886 - sparse_categorical_crossentropy: 0.0197 - sparse_categorical_accuracy: 0.9939 - scaled_adversarial_loss: 0.0689 - val_loss: 0.0831 - val_sparse_categorical_crossentropy: 0.0315 - val_sparse_categorical_accuracy: 0.9888 - val_scaled_adversarial_loss: 0.0515\n",
      "Epoch 872/1000\n",
      "12/12 [==============================] - 5s 379ms/step - loss: 0.1003 - sparse_categorical_crossentropy: 0.0275 - sparse_categorical_accuracy: 0.9911 - scaled_adversarial_loss: 0.0728 - val_loss: 0.0899 - val_sparse_categorical_crossentropy: 0.0370 - val_sparse_categorical_accuracy: 0.9881 - val_scaled_adversarial_loss: 0.0529\n",
      "Epoch 873/1000\n",
      "12/12 [==============================] - 5s 392ms/step - loss: 0.0994 - sparse_categorical_crossentropy: 0.0275 - sparse_categorical_accuracy: 0.9913 - scaled_adversarial_loss: 0.0720 - val_loss: 0.0810 - val_sparse_categorical_crossentropy: 0.0351 - val_sparse_categorical_accuracy: 0.9923 - val_scaled_adversarial_loss: 0.0459\n",
      "Epoch 874/1000\n",
      "12/12 [==============================] - 5s 380ms/step - loss: 0.0970 - sparse_categorical_crossentropy: 0.0283 - sparse_categorical_accuracy: 0.9897 - scaled_adversarial_loss: 0.0687 - val_loss: 0.0906 - val_sparse_categorical_crossentropy: 0.0359 - val_sparse_categorical_accuracy: 0.9895 - val_scaled_adversarial_loss: 0.0547\n",
      "Epoch 875/1000\n",
      "12/12 [==============================] - 5s 383ms/step - loss: 0.1105 - sparse_categorical_crossentropy: 0.0334 - sparse_categorical_accuracy: 0.9902 - scaled_adversarial_loss: 0.0771 - val_loss: 0.0849 - val_sparse_categorical_crossentropy: 0.0302 - val_sparse_categorical_accuracy: 0.9902 - val_scaled_adversarial_loss: 0.0547\n",
      "Epoch 876/1000\n",
      "12/12 [==============================] - 4s 370ms/step - loss: 0.1043 - sparse_categorical_crossentropy: 0.0288 - sparse_categorical_accuracy: 0.9923 - scaled_adversarial_loss: 0.0755 - val_loss: 0.0811 - val_sparse_categorical_crossentropy: 0.0322 - val_sparse_categorical_accuracy: 0.9902 - val_scaled_adversarial_loss: 0.0489\n",
      "Epoch 877/1000\n",
      "12/12 [==============================] - 4s 367ms/step - loss: 0.0987 - sparse_categorical_crossentropy: 0.0257 - sparse_categorical_accuracy: 0.9913 - scaled_adversarial_loss: 0.0730 - val_loss: 0.0896 - val_sparse_categorical_crossentropy: 0.0399 - val_sparse_categorical_accuracy: 0.9895 - val_scaled_adversarial_loss: 0.0497\n",
      "Epoch 878/1000\n",
      "12/12 [==============================] - 5s 380ms/step - loss: 0.1028 - sparse_categorical_crossentropy: 0.0259 - sparse_categorical_accuracy: 0.9907 - scaled_adversarial_loss: 0.0769 - val_loss: 0.0852 - val_sparse_categorical_crossentropy: 0.0310 - val_sparse_categorical_accuracy: 0.9909 - val_scaled_adversarial_loss: 0.0543\n",
      "Epoch 879/1000\n",
      "12/12 [==============================] - 5s 379ms/step - loss: 0.0981 - sparse_categorical_crossentropy: 0.0276 - sparse_categorical_accuracy: 0.9890 - scaled_adversarial_loss: 0.0705 - val_loss: 0.0992 - val_sparse_categorical_crossentropy: 0.0364 - val_sparse_categorical_accuracy: 0.9902 - val_scaled_adversarial_loss: 0.0628\n",
      "Epoch 880/1000\n",
      "12/12 [==============================] - 5s 405ms/step - loss: 0.0977 - sparse_categorical_crossentropy: 0.0242 - sparse_categorical_accuracy: 0.9906 - scaled_adversarial_loss: 0.0735 - val_loss: 0.0950 - val_sparse_categorical_crossentropy: 0.0417 - val_sparse_categorical_accuracy: 0.9902 - val_scaled_adversarial_loss: 0.0533\n",
      "Epoch 881/1000\n",
      "12/12 [==============================] - 5s 382ms/step - loss: 0.0997 - sparse_categorical_crossentropy: 0.0265 - sparse_categorical_accuracy: 0.9895 - scaled_adversarial_loss: 0.0732 - val_loss: 0.0899 - val_sparse_categorical_crossentropy: 0.0370 - val_sparse_categorical_accuracy: 0.9895 - val_scaled_adversarial_loss: 0.0529\n",
      "Epoch 882/1000\n",
      "12/12 [==============================] - 5s 379ms/step - loss: 0.1021 - sparse_categorical_crossentropy: 0.0325 - sparse_categorical_accuracy: 0.9904 - scaled_adversarial_loss: 0.0696 - val_loss: 0.0923 - val_sparse_categorical_crossentropy: 0.0324 - val_sparse_categorical_accuracy: 0.9923 - val_scaled_adversarial_loss: 0.0599\n",
      "Epoch 883/1000\n",
      "12/12 [==============================] - 5s 380ms/step - loss: 0.0937 - sparse_categorical_crossentropy: 0.0234 - sparse_categorical_accuracy: 0.9930 - scaled_adversarial_loss: 0.0703 - val_loss: 0.0868 - val_sparse_categorical_crossentropy: 0.0349 - val_sparse_categorical_accuracy: 0.9888 - val_scaled_adversarial_loss: 0.0519\n",
      "Epoch 884/1000\n",
      "12/12 [==============================] - 4s 376ms/step - loss: 0.0983 - sparse_categorical_crossentropy: 0.0272 - sparse_categorical_accuracy: 0.9900 - scaled_adversarial_loss: 0.0711 - val_loss: 0.0839 - val_sparse_categorical_crossentropy: 0.0366 - val_sparse_categorical_accuracy: 0.9874 - val_scaled_adversarial_loss: 0.0474\n",
      "Epoch 885/1000\n",
      "12/12 [==============================] - 5s 378ms/step - loss: 0.0868 - sparse_categorical_crossentropy: 0.0189 - sparse_categorical_accuracy: 0.9927 - scaled_adversarial_loss: 0.0678 - val_loss: 0.0919 - val_sparse_categorical_crossentropy: 0.0430 - val_sparse_categorical_accuracy: 0.9874 - val_scaled_adversarial_loss: 0.0490\n",
      "Epoch 886/1000\n",
      "12/12 [==============================] - 4s 370ms/step - loss: 0.0936 - sparse_categorical_crossentropy: 0.0224 - sparse_categorical_accuracy: 0.9930 - scaled_adversarial_loss: 0.0712 - val_loss: 0.0868 - val_sparse_categorical_crossentropy: 0.0376 - val_sparse_categorical_accuracy: 0.9916 - val_scaled_adversarial_loss: 0.0492\n",
      "Epoch 887/1000\n",
      "12/12 [==============================] - 5s 380ms/step - loss: 0.0945 - sparse_categorical_crossentropy: 0.0265 - sparse_categorical_accuracy: 0.9899 - scaled_adversarial_loss: 0.0680 - val_loss: 0.0931 - val_sparse_categorical_crossentropy: 0.0318 - val_sparse_categorical_accuracy: 0.9916 - val_scaled_adversarial_loss: 0.0612\n",
      "Epoch 888/1000\n",
      "12/12 [==============================] - 5s 389ms/step - loss: 0.1114 - sparse_categorical_crossentropy: 0.0399 - sparse_categorical_accuracy: 0.9886 - scaled_adversarial_loss: 0.0715 - val_loss: 0.0789 - val_sparse_categorical_crossentropy: 0.0351 - val_sparse_categorical_accuracy: 0.9909 - val_scaled_adversarial_loss: 0.0438\n",
      "Epoch 889/1000\n",
      "12/12 [==============================] - 5s 390ms/step - loss: 0.1073 - sparse_categorical_crossentropy: 0.0286 - sparse_categorical_accuracy: 0.9902 - scaled_adversarial_loss: 0.0787 - val_loss: 0.0850 - val_sparse_categorical_crossentropy: 0.0383 - val_sparse_categorical_accuracy: 0.9902 - val_scaled_adversarial_loss: 0.0467\n",
      "Epoch 890/1000\n",
      "12/12 [==============================] - 5s 395ms/step - loss: 0.1080 - sparse_categorical_crossentropy: 0.0327 - sparse_categorical_accuracy: 0.9897 - scaled_adversarial_loss: 0.0753 - val_loss: 0.0806 - val_sparse_categorical_crossentropy: 0.0333 - val_sparse_categorical_accuracy: 0.9930 - val_scaled_adversarial_loss: 0.0474\n",
      "Epoch 891/1000\n",
      "12/12 [==============================] - 5s 383ms/step - loss: 0.1007 - sparse_categorical_crossentropy: 0.0300 - sparse_categorical_accuracy: 0.9911 - scaled_adversarial_loss: 0.0707 - val_loss: 0.0783 - val_sparse_categorical_crossentropy: 0.0390 - val_sparse_categorical_accuracy: 0.9916 - val_scaled_adversarial_loss: 0.0393\n",
      "Epoch 892/1000\n",
      "12/12 [==============================] - 5s 387ms/step - loss: 0.1340 - sparse_categorical_crossentropy: 0.0551 - sparse_categorical_accuracy: 0.9823 - scaled_adversarial_loss: 0.0790 - val_loss: 0.0949 - val_sparse_categorical_crossentropy: 0.0413 - val_sparse_categorical_accuracy: 0.9895 - val_scaled_adversarial_loss: 0.0536\n",
      "Epoch 893/1000\n",
      "12/12 [==============================] - 5s 390ms/step - loss: 0.1236 - sparse_categorical_crossentropy: 0.0468 - sparse_categorical_accuracy: 0.9848 - scaled_adversarial_loss: 0.0768 - val_loss: 0.0894 - val_sparse_categorical_crossentropy: 0.0349 - val_sparse_categorical_accuracy: 0.9909 - val_scaled_adversarial_loss: 0.0545\n",
      "Epoch 894/1000\n",
      "12/12 [==============================] - 5s 385ms/step - loss: 0.1089 - sparse_categorical_crossentropy: 0.0338 - sparse_categorical_accuracy: 0.9893 - scaled_adversarial_loss: 0.0751 - val_loss: 0.0836 - val_sparse_categorical_crossentropy: 0.0409 - val_sparse_categorical_accuracy: 0.9888 - val_scaled_adversarial_loss: 0.0427\n",
      "Epoch 895/1000\n",
      "12/12 [==============================] - 5s 379ms/step - loss: 0.1174 - sparse_categorical_crossentropy: 0.0386 - sparse_categorical_accuracy: 0.9872 - scaled_adversarial_loss: 0.0788 - val_loss: 0.0823 - val_sparse_categorical_crossentropy: 0.0337 - val_sparse_categorical_accuracy: 0.9867 - val_scaled_adversarial_loss: 0.0486\n",
      "Epoch 896/1000\n",
      "12/12 [==============================] - 4s 377ms/step - loss: 0.1109 - sparse_categorical_crossentropy: 0.0372 - sparse_categorical_accuracy: 0.9886 - scaled_adversarial_loss: 0.0737 - val_loss: 0.0875 - val_sparse_categorical_crossentropy: 0.0365 - val_sparse_categorical_accuracy: 0.9916 - val_scaled_adversarial_loss: 0.0510\n",
      "Epoch 897/1000\n",
      "12/12 [==============================] - 4s 366ms/step - loss: 0.1003 - sparse_categorical_crossentropy: 0.0283 - sparse_categorical_accuracy: 0.9899 - scaled_adversarial_loss: 0.0719 - val_loss: 0.0875 - val_sparse_categorical_crossentropy: 0.0330 - val_sparse_categorical_accuracy: 0.9909 - val_scaled_adversarial_loss: 0.0544\n",
      "Epoch 898/1000\n",
      "12/12 [==============================] - 5s 388ms/step - loss: 0.1039 - sparse_categorical_crossentropy: 0.0295 - sparse_categorical_accuracy: 0.9888 - scaled_adversarial_loss: 0.0744 - val_loss: 0.0790 - val_sparse_categorical_crossentropy: 0.0386 - val_sparse_categorical_accuracy: 0.9902 - val_scaled_adversarial_loss: 0.0404\n",
      "Epoch 899/1000\n",
      "12/12 [==============================] - 5s 388ms/step - loss: 0.0971 - sparse_categorical_crossentropy: 0.0245 - sparse_categorical_accuracy: 0.9907 - scaled_adversarial_loss: 0.0727 - val_loss: 0.0759 - val_sparse_categorical_crossentropy: 0.0336 - val_sparse_categorical_accuracy: 0.9923 - val_scaled_adversarial_loss: 0.0423\n",
      "Epoch 900/1000\n",
      "12/12 [==============================] - 5s 397ms/step - loss: 0.0998 - sparse_categorical_crossentropy: 0.0268 - sparse_categorical_accuracy: 0.9913 - scaled_adversarial_loss: 0.0729 - val_loss: 0.0934 - val_sparse_categorical_crossentropy: 0.0352 - val_sparse_categorical_accuracy: 0.9895 - val_scaled_adversarial_loss: 0.0582\n",
      "Epoch 901/1000\n",
      "12/12 [==============================] - 5s 382ms/step - loss: 0.0960 - sparse_categorical_crossentropy: 0.0231 - sparse_categorical_accuracy: 0.9913 - scaled_adversarial_loss: 0.0729 - val_loss: 0.0801 - val_sparse_categorical_crossentropy: 0.0332 - val_sparse_categorical_accuracy: 0.9923 - val_scaled_adversarial_loss: 0.0469\n",
      "Epoch 902/1000\n",
      "12/12 [==============================] - 5s 378ms/step - loss: 0.0963 - sparse_categorical_crossentropy: 0.0262 - sparse_categorical_accuracy: 0.9918 - scaled_adversarial_loss: 0.0702 - val_loss: 0.0879 - val_sparse_categorical_crossentropy: 0.0345 - val_sparse_categorical_accuracy: 0.9916 - val_scaled_adversarial_loss: 0.0533\n",
      "Epoch 903/1000\n",
      "12/12 [==============================] - 5s 384ms/step - loss: 0.0995 - sparse_categorical_crossentropy: 0.0277 - sparse_categorical_accuracy: 0.9909 - scaled_adversarial_loss: 0.0718 - val_loss: 0.0825 - val_sparse_categorical_crossentropy: 0.0354 - val_sparse_categorical_accuracy: 0.9895 - val_scaled_adversarial_loss: 0.0471\n",
      "Epoch 904/1000\n",
      "12/12 [==============================] - 5s 396ms/step - loss: 0.0957 - sparse_categorical_crossentropy: 0.0244 - sparse_categorical_accuracy: 0.9916 - scaled_adversarial_loss: 0.0714 - val_loss: 0.0850 - val_sparse_categorical_crossentropy: 0.0300 - val_sparse_categorical_accuracy: 0.9916 - val_scaled_adversarial_loss: 0.0550\n",
      "Epoch 905/1000\n",
      "12/12 [==============================] - 5s 390ms/step - loss: 0.0855 - sparse_categorical_crossentropy: 0.0191 - sparse_categorical_accuracy: 0.9932 - scaled_adversarial_loss: 0.0664 - val_loss: 0.0715 - val_sparse_categorical_crossentropy: 0.0290 - val_sparse_categorical_accuracy: 0.9930 - val_scaled_adversarial_loss: 0.0425\n",
      "Epoch 906/1000\n",
      "12/12 [==============================] - 5s 384ms/step - loss: 0.0930 - sparse_categorical_crossentropy: 0.0234 - sparse_categorical_accuracy: 0.9914 - scaled_adversarial_loss: 0.0696 - val_loss: 0.0745 - val_sparse_categorical_crossentropy: 0.0331 - val_sparse_categorical_accuracy: 0.9916 - val_scaled_adversarial_loss: 0.0414\n",
      "Epoch 907/1000\n",
      "12/12 [==============================] - 5s 382ms/step - loss: 0.1040 - sparse_categorical_crossentropy: 0.0274 - sparse_categorical_accuracy: 0.9918 - scaled_adversarial_loss: 0.0766 - val_loss: 0.0846 - val_sparse_categorical_crossentropy: 0.0281 - val_sparse_categorical_accuracy: 0.9937 - val_scaled_adversarial_loss: 0.0566\n",
      "Epoch 908/1000\n",
      "12/12 [==============================] - 5s 390ms/step - loss: 0.1035 - sparse_categorical_crossentropy: 0.0266 - sparse_categorical_accuracy: 0.9906 - scaled_adversarial_loss: 0.0769 - val_loss: 0.0756 - val_sparse_categorical_crossentropy: 0.0306 - val_sparse_categorical_accuracy: 0.9923 - val_scaled_adversarial_loss: 0.0450\n",
      "Epoch 909/1000\n",
      "12/12 [==============================] - 5s 380ms/step - loss: 0.0951 - sparse_categorical_crossentropy: 0.0275 - sparse_categorical_accuracy: 0.9897 - scaled_adversarial_loss: 0.0677 - val_loss: 0.0940 - val_sparse_categorical_crossentropy: 0.0364 - val_sparse_categorical_accuracy: 0.9881 - val_scaled_adversarial_loss: 0.0575\n",
      "Epoch 910/1000\n",
      "12/12 [==============================] - 5s 387ms/step - loss: 0.0968 - sparse_categorical_crossentropy: 0.0270 - sparse_categorical_accuracy: 0.9909 - scaled_adversarial_loss: 0.0698 - val_loss: 0.0823 - val_sparse_categorical_crossentropy: 0.0331 - val_sparse_categorical_accuracy: 0.9902 - val_scaled_adversarial_loss: 0.0492\n",
      "Epoch 911/1000\n",
      "12/12 [==============================] - 5s 391ms/step - loss: 0.1054 - sparse_categorical_crossentropy: 0.0304 - sparse_categorical_accuracy: 0.9902 - scaled_adversarial_loss: 0.0751 - val_loss: 0.0889 - val_sparse_categorical_crossentropy: 0.0294 - val_sparse_categorical_accuracy: 0.9895 - val_scaled_adversarial_loss: 0.0594\n",
      "Epoch 912/1000\n",
      "12/12 [==============================] - 5s 380ms/step - loss: 0.1026 - sparse_categorical_crossentropy: 0.0287 - sparse_categorical_accuracy: 0.9906 - scaled_adversarial_loss: 0.0739 - val_loss: 0.0868 - val_sparse_categorical_crossentropy: 0.0336 - val_sparse_categorical_accuracy: 0.9916 - val_scaled_adversarial_loss: 0.0532\n",
      "Epoch 913/1000\n",
      "12/12 [==============================] - 5s 389ms/step - loss: 0.0952 - sparse_categorical_crossentropy: 0.0229 - sparse_categorical_accuracy: 0.9923 - scaled_adversarial_loss: 0.0723 - val_loss: 0.0842 - val_sparse_categorical_crossentropy: 0.0371 - val_sparse_categorical_accuracy: 0.9888 - val_scaled_adversarial_loss: 0.0472\n",
      "Epoch 914/1000\n",
      "12/12 [==============================] - 5s 379ms/step - loss: 0.1084 - sparse_categorical_crossentropy: 0.0328 - sparse_categorical_accuracy: 0.9879 - scaled_adversarial_loss: 0.0756 - val_loss: 0.0778 - val_sparse_categorical_crossentropy: 0.0366 - val_sparse_categorical_accuracy: 0.9916 - val_scaled_adversarial_loss: 0.0412\n",
      "Epoch 915/1000\n",
      "12/12 [==============================] - 5s 385ms/step - loss: 0.1088 - sparse_categorical_crossentropy: 0.0367 - sparse_categorical_accuracy: 0.9890 - scaled_adversarial_loss: 0.0722 - val_loss: 0.0791 - val_sparse_categorical_crossentropy: 0.0268 - val_sparse_categorical_accuracy: 0.9923 - val_scaled_adversarial_loss: 0.0523\n",
      "Epoch 916/1000\n",
      "12/12 [==============================] - 5s 383ms/step - loss: 0.1011 - sparse_categorical_crossentropy: 0.0304 - sparse_categorical_accuracy: 0.9904 - scaled_adversarial_loss: 0.0707 - val_loss: 0.0789 - val_sparse_categorical_crossentropy: 0.0310 - val_sparse_categorical_accuracy: 0.9916 - val_scaled_adversarial_loss: 0.0479\n",
      "Epoch 917/1000\n",
      "12/12 [==============================] - 5s 377ms/step - loss: 0.1076 - sparse_categorical_crossentropy: 0.0368 - sparse_categorical_accuracy: 0.9883 - scaled_adversarial_loss: 0.0709 - val_loss: 0.0911 - val_sparse_categorical_crossentropy: 0.0436 - val_sparse_categorical_accuracy: 0.9867 - val_scaled_adversarial_loss: 0.0475\n",
      "Epoch 918/1000\n",
      "12/12 [==============================] - 5s 400ms/step - loss: 0.1279 - sparse_categorical_crossentropy: 0.0450 - sparse_categorical_accuracy: 0.9851 - scaled_adversarial_loss: 0.0830 - val_loss: 0.1047 - val_sparse_categorical_crossentropy: 0.0498 - val_sparse_categorical_accuracy: 0.9860 - val_scaled_adversarial_loss: 0.0548\n",
      "Epoch 919/1000\n",
      "12/12 [==============================] - 5s 454ms/step - loss: 0.1163 - sparse_categorical_crossentropy: 0.0356 - sparse_categorical_accuracy: 0.9871 - scaled_adversarial_loss: 0.0807 - val_loss: 0.0976 - val_sparse_categorical_crossentropy: 0.0369 - val_sparse_categorical_accuracy: 0.9874 - val_scaled_adversarial_loss: 0.0606\n",
      "Epoch 920/1000\n",
      "12/12 [==============================] - 5s 456ms/step - loss: 0.0970 - sparse_categorical_crossentropy: 0.0270 - sparse_categorical_accuracy: 0.9881 - scaled_adversarial_loss: 0.0700 - val_loss: 0.1090 - val_sparse_categorical_crossentropy: 0.0423 - val_sparse_categorical_accuracy: 0.9888 - val_scaled_adversarial_loss: 0.0667\n",
      "Epoch 921/1000\n",
      "12/12 [==============================] - 5s 462ms/step - loss: 0.1028 - sparse_categorical_crossentropy: 0.0278 - sparse_categorical_accuracy: 0.9904 - scaled_adversarial_loss: 0.0749 - val_loss: 0.0806 - val_sparse_categorical_crossentropy: 0.0325 - val_sparse_categorical_accuracy: 0.9916 - val_scaled_adversarial_loss: 0.0480\n",
      "Epoch 922/1000\n",
      "12/12 [==============================] - 5s 459ms/step - loss: 0.1062 - sparse_categorical_crossentropy: 0.0313 - sparse_categorical_accuracy: 0.9904 - scaled_adversarial_loss: 0.0749 - val_loss: 0.0809 - val_sparse_categorical_crossentropy: 0.0333 - val_sparse_categorical_accuracy: 0.9902 - val_scaled_adversarial_loss: 0.0476\n",
      "Epoch 923/1000\n",
      "12/12 [==============================] - 6s 466ms/step - loss: 0.1164 - sparse_categorical_crossentropy: 0.0396 - sparse_categorical_accuracy: 0.9883 - scaled_adversarial_loss: 0.0768 - val_loss: 0.0775 - val_sparse_categorical_crossentropy: 0.0349 - val_sparse_categorical_accuracy: 0.9916 - val_scaled_adversarial_loss: 0.0426\n",
      "Epoch 924/1000\n",
      "12/12 [==============================] - 6s 476ms/step - loss: 0.1077 - sparse_categorical_crossentropy: 0.0331 - sparse_categorical_accuracy: 0.9869 - scaled_adversarial_loss: 0.0746 - val_loss: 0.0824 - val_sparse_categorical_crossentropy: 0.0323 - val_sparse_categorical_accuracy: 0.9909 - val_scaled_adversarial_loss: 0.0500\n",
      "Epoch 925/1000\n",
      "12/12 [==============================] - 6s 481ms/step - loss: 0.1053 - sparse_categorical_crossentropy: 0.0313 - sparse_categorical_accuracy: 0.9893 - scaled_adversarial_loss: 0.0740 - val_loss: 0.0855 - val_sparse_categorical_crossentropy: 0.0307 - val_sparse_categorical_accuracy: 0.9909 - val_scaled_adversarial_loss: 0.0548\n",
      "Epoch 926/1000\n",
      "12/12 [==============================] - 6s 474ms/step - loss: 0.1128 - sparse_categorical_crossentropy: 0.0354 - sparse_categorical_accuracy: 0.9892 - scaled_adversarial_loss: 0.0774 - val_loss: 0.1007 - val_sparse_categorical_crossentropy: 0.0388 - val_sparse_categorical_accuracy: 0.9874 - val_scaled_adversarial_loss: 0.0619\n",
      "Epoch 927/1000\n",
      "12/12 [==============================] - 6s 474ms/step - loss: 0.1176 - sparse_categorical_crossentropy: 0.0355 - sparse_categorical_accuracy: 0.9881 - scaled_adversarial_loss: 0.0820 - val_loss: 0.0834 - val_sparse_categorical_crossentropy: 0.0323 - val_sparse_categorical_accuracy: 0.9902 - val_scaled_adversarial_loss: 0.0511\n",
      "Epoch 928/1000\n",
      "12/12 [==============================] - 6s 464ms/step - loss: 0.1033 - sparse_categorical_crossentropy: 0.0279 - sparse_categorical_accuracy: 0.9913 - scaled_adversarial_loss: 0.0754 - val_loss: 0.0781 - val_sparse_categorical_crossentropy: 0.0307 - val_sparse_categorical_accuracy: 0.9895 - val_scaled_adversarial_loss: 0.0474\n",
      "Epoch 929/1000\n",
      "12/12 [==============================] - 6s 467ms/step - loss: 0.1106 - sparse_categorical_crossentropy: 0.0371 - sparse_categorical_accuracy: 0.9890 - scaled_adversarial_loss: 0.0735 - val_loss: 0.0912 - val_sparse_categorical_crossentropy: 0.0304 - val_sparse_categorical_accuracy: 0.9902 - val_scaled_adversarial_loss: 0.0608\n",
      "Epoch 930/1000\n",
      "12/12 [==============================] - 6s 477ms/step - loss: 0.1096 - sparse_categorical_crossentropy: 0.0364 - sparse_categorical_accuracy: 0.9881 - scaled_adversarial_loss: 0.0732 - val_loss: 0.0817 - val_sparse_categorical_crossentropy: 0.0284 - val_sparse_categorical_accuracy: 0.9923 - val_scaled_adversarial_loss: 0.0533\n",
      "Epoch 931/1000\n",
      "12/12 [==============================] - 6s 472ms/step - loss: 0.1047 - sparse_categorical_crossentropy: 0.0335 - sparse_categorical_accuracy: 0.9895 - scaled_adversarial_loss: 0.0712 - val_loss: 0.0775 - val_sparse_categorical_crossentropy: 0.0259 - val_sparse_categorical_accuracy: 0.9902 - val_scaled_adversarial_loss: 0.0516\n",
      "Epoch 932/1000\n",
      "12/12 [==============================] - 6s 473ms/step - loss: 0.1018 - sparse_categorical_crossentropy: 0.0312 - sparse_categorical_accuracy: 0.9906 - scaled_adversarial_loss: 0.0706 - val_loss: 0.0722 - val_sparse_categorical_crossentropy: 0.0296 - val_sparse_categorical_accuracy: 0.9909 - val_scaled_adversarial_loss: 0.0426\n",
      "Epoch 933/1000\n",
      "12/12 [==============================] - 6s 477ms/step - loss: 0.0999 - sparse_categorical_crossentropy: 0.0248 - sparse_categorical_accuracy: 0.9927 - scaled_adversarial_loss: 0.0750 - val_loss: 0.0803 - val_sparse_categorical_crossentropy: 0.0298 - val_sparse_categorical_accuracy: 0.9895 - val_scaled_adversarial_loss: 0.0506\n",
      "Epoch 934/1000\n",
      "12/12 [==============================] - 6s 471ms/step - loss: 0.0963 - sparse_categorical_crossentropy: 0.0267 - sparse_categorical_accuracy: 0.9906 - scaled_adversarial_loss: 0.0697 - val_loss: 0.0767 - val_sparse_categorical_crossentropy: 0.0330 - val_sparse_categorical_accuracy: 0.9902 - val_scaled_adversarial_loss: 0.0436\n",
      "Epoch 935/1000\n",
      "12/12 [==============================] - 6s 505ms/step - loss: 0.0957 - sparse_categorical_crossentropy: 0.0222 - sparse_categorical_accuracy: 0.9927 - scaled_adversarial_loss: 0.0734 - val_loss: 0.0847 - val_sparse_categorical_crossentropy: 0.0317 - val_sparse_categorical_accuracy: 0.9909 - val_scaled_adversarial_loss: 0.0530\n",
      "Epoch 936/1000\n",
      "12/12 [==============================] - 6s 470ms/step - loss: 0.0925 - sparse_categorical_crossentropy: 0.0224 - sparse_categorical_accuracy: 0.9923 - scaled_adversarial_loss: 0.0701 - val_loss: 0.0792 - val_sparse_categorical_crossentropy: 0.0300 - val_sparse_categorical_accuracy: 0.9916 - val_scaled_adversarial_loss: 0.0492\n",
      "Epoch 937/1000\n",
      "12/12 [==============================] - 6s 470ms/step - loss: 0.0952 - sparse_categorical_crossentropy: 0.0209 - sparse_categorical_accuracy: 0.9920 - scaled_adversarial_loss: 0.0743 - val_loss: 0.0876 - val_sparse_categorical_crossentropy: 0.0325 - val_sparse_categorical_accuracy: 0.9909 - val_scaled_adversarial_loss: 0.0550\n",
      "Epoch 938/1000\n",
      "12/12 [==============================] - 6s 476ms/step - loss: 0.0913 - sparse_categorical_crossentropy: 0.0226 - sparse_categorical_accuracy: 0.9935 - scaled_adversarial_loss: 0.0687 - val_loss: 0.0819 - val_sparse_categorical_crossentropy: 0.0350 - val_sparse_categorical_accuracy: 0.9902 - val_scaled_adversarial_loss: 0.0469\n",
      "Epoch 939/1000\n",
      "12/12 [==============================] - 6s 468ms/step - loss: 0.1055 - sparse_categorical_crossentropy: 0.0337 - sparse_categorical_accuracy: 0.9888 - scaled_adversarial_loss: 0.0718 - val_loss: 0.0846 - val_sparse_categorical_crossentropy: 0.0354 - val_sparse_categorical_accuracy: 0.9881 - val_scaled_adversarial_loss: 0.0492\n",
      "Epoch 940/1000\n",
      "12/12 [==============================] - 6s 472ms/step - loss: 0.1077 - sparse_categorical_crossentropy: 0.0342 - sparse_categorical_accuracy: 0.9890 - scaled_adversarial_loss: 0.0735 - val_loss: 0.0840 - val_sparse_categorical_crossentropy: 0.0319 - val_sparse_categorical_accuracy: 0.9902 - val_scaled_adversarial_loss: 0.0521\n",
      "Epoch 941/1000\n",
      "12/12 [==============================] - 6s 480ms/step - loss: 0.1001 - sparse_categorical_crossentropy: 0.0292 - sparse_categorical_accuracy: 0.9904 - scaled_adversarial_loss: 0.0709 - val_loss: 0.0797 - val_sparse_categorical_crossentropy: 0.0341 - val_sparse_categorical_accuracy: 0.9916 - val_scaled_adversarial_loss: 0.0455\n",
      "Epoch 942/1000\n",
      "12/12 [==============================] - 6s 476ms/step - loss: 0.0988 - sparse_categorical_crossentropy: 0.0296 - sparse_categorical_accuracy: 0.9914 - scaled_adversarial_loss: 0.0692 - val_loss: 0.0833 - val_sparse_categorical_crossentropy: 0.0321 - val_sparse_categorical_accuracy: 0.9916 - val_scaled_adversarial_loss: 0.0512\n",
      "Epoch 943/1000\n",
      "12/12 [==============================] - 6s 472ms/step - loss: 0.0991 - sparse_categorical_crossentropy: 0.0263 - sparse_categorical_accuracy: 0.9888 - scaled_adversarial_loss: 0.0729 - val_loss: 0.0819 - val_sparse_categorical_crossentropy: 0.0280 - val_sparse_categorical_accuracy: 0.9930 - val_scaled_adversarial_loss: 0.0539\n",
      "Epoch 944/1000\n",
      "12/12 [==============================] - 6s 464ms/step - loss: 0.1045 - sparse_categorical_crossentropy: 0.0306 - sparse_categorical_accuracy: 0.9913 - scaled_adversarial_loss: 0.0739 - val_loss: 0.0865 - val_sparse_categorical_crossentropy: 0.0312 - val_sparse_categorical_accuracy: 0.9909 - val_scaled_adversarial_loss: 0.0553\n",
      "Epoch 945/1000\n",
      "12/12 [==============================] - 6s 469ms/step - loss: 0.0957 - sparse_categorical_crossentropy: 0.0281 - sparse_categorical_accuracy: 0.9911 - scaled_adversarial_loss: 0.0676 - val_loss: 0.0751 - val_sparse_categorical_crossentropy: 0.0301 - val_sparse_categorical_accuracy: 0.9909 - val_scaled_adversarial_loss: 0.0450\n",
      "Epoch 946/1000\n",
      "12/12 [==============================] - 6s 480ms/step - loss: 0.0986 - sparse_categorical_crossentropy: 0.0292 - sparse_categorical_accuracy: 0.9902 - scaled_adversarial_loss: 0.0694 - val_loss: 0.0816 - val_sparse_categorical_crossentropy: 0.0335 - val_sparse_categorical_accuracy: 0.9902 - val_scaled_adversarial_loss: 0.0481\n",
      "Epoch 947/1000\n",
      "12/12 [==============================] - 6s 476ms/step - loss: 0.0995 - sparse_categorical_crossentropy: 0.0265 - sparse_categorical_accuracy: 0.9909 - scaled_adversarial_loss: 0.0729 - val_loss: 0.0928 - val_sparse_categorical_crossentropy: 0.0353 - val_sparse_categorical_accuracy: 0.9881 - val_scaled_adversarial_loss: 0.0575\n",
      "Epoch 948/1000\n",
      "12/12 [==============================] - 5s 449ms/step - loss: 0.1061 - sparse_categorical_crossentropy: 0.0335 - sparse_categorical_accuracy: 0.9911 - scaled_adversarial_loss: 0.0726 - val_loss: 0.0905 - val_sparse_categorical_crossentropy: 0.0329 - val_sparse_categorical_accuracy: 0.9888 - val_scaled_adversarial_loss: 0.0576\n",
      "Epoch 949/1000\n",
      "12/12 [==============================] - 5s 403ms/step - loss: 0.0954 - sparse_categorical_crossentropy: 0.0217 - sparse_categorical_accuracy: 0.9927 - scaled_adversarial_loss: 0.0737 - val_loss: 0.0842 - val_sparse_categorical_crossentropy: 0.0364 - val_sparse_categorical_accuracy: 0.9888 - val_scaled_adversarial_loss: 0.0478\n",
      "Epoch 950/1000\n",
      "12/12 [==============================] - 5s 403ms/step - loss: 0.0912 - sparse_categorical_crossentropy: 0.0226 - sparse_categorical_accuracy: 0.9916 - scaled_adversarial_loss: 0.0686 - val_loss: 0.0897 - val_sparse_categorical_crossentropy: 0.0395 - val_sparse_categorical_accuracy: 0.9895 - val_scaled_adversarial_loss: 0.0501\n",
      "Epoch 951/1000\n",
      "12/12 [==============================] - 5s 427ms/step - loss: 0.0921 - sparse_categorical_crossentropy: 0.0229 - sparse_categorical_accuracy: 0.9913 - scaled_adversarial_loss: 0.0693 - val_loss: 0.0874 - val_sparse_categorical_crossentropy: 0.0364 - val_sparse_categorical_accuracy: 0.9902 - val_scaled_adversarial_loss: 0.0510\n",
      "Epoch 952/1000\n",
      "12/12 [==============================] - 5s 434ms/step - loss: 0.1064 - sparse_categorical_crossentropy: 0.0334 - sparse_categorical_accuracy: 0.9897 - scaled_adversarial_loss: 0.0729 - val_loss: 0.0834 - val_sparse_categorical_crossentropy: 0.0421 - val_sparse_categorical_accuracy: 0.9888 - val_scaled_adversarial_loss: 0.0413\n",
      "Epoch 953/1000\n",
      "12/12 [==============================] - 5s 461ms/step - loss: 0.1004 - sparse_categorical_crossentropy: 0.0290 - sparse_categorical_accuracy: 0.9913 - scaled_adversarial_loss: 0.0713 - val_loss: 0.0744 - val_sparse_categorical_crossentropy: 0.0343 - val_sparse_categorical_accuracy: 0.9902 - val_scaled_adversarial_loss: 0.0401\n",
      "Epoch 954/1000\n",
      "12/12 [==============================] - 5s 453ms/step - loss: 0.1001 - sparse_categorical_crossentropy: 0.0289 - sparse_categorical_accuracy: 0.9897 - scaled_adversarial_loss: 0.0713 - val_loss: 0.0832 - val_sparse_categorical_crossentropy: 0.0374 - val_sparse_categorical_accuracy: 0.9923 - val_scaled_adversarial_loss: 0.0458\n",
      "Epoch 955/1000\n",
      "12/12 [==============================] - 5s 457ms/step - loss: 0.0998 - sparse_categorical_crossentropy: 0.0275 - sparse_categorical_accuracy: 0.9930 - scaled_adversarial_loss: 0.0724 - val_loss: 0.0854 - val_sparse_categorical_crossentropy: 0.0398 - val_sparse_categorical_accuracy: 0.9895 - val_scaled_adversarial_loss: 0.0456\n",
      "Epoch 956/1000\n",
      "12/12 [==============================] - 6s 465ms/step - loss: 0.1011 - sparse_categorical_crossentropy: 0.0271 - sparse_categorical_accuracy: 0.9909 - scaled_adversarial_loss: 0.0740 - val_loss: 0.0759 - val_sparse_categorical_crossentropy: 0.0324 - val_sparse_categorical_accuracy: 0.9909 - val_scaled_adversarial_loss: 0.0435\n",
      "Epoch 957/1000\n",
      "12/12 [==============================] - 6s 496ms/step - loss: 0.0875 - sparse_categorical_crossentropy: 0.0220 - sparse_categorical_accuracy: 0.9934 - scaled_adversarial_loss: 0.0656 - val_loss: 0.0828 - val_sparse_categorical_crossentropy: 0.0287 - val_sparse_categorical_accuracy: 0.9902 - val_scaled_adversarial_loss: 0.0540\n",
      "Epoch 958/1000\n",
      "12/12 [==============================] - 6s 461ms/step - loss: 0.0997 - sparse_categorical_crossentropy: 0.0264 - sparse_categorical_accuracy: 0.9909 - scaled_adversarial_loss: 0.0734 - val_loss: 0.0887 - val_sparse_categorical_crossentropy: 0.0332 - val_sparse_categorical_accuracy: 0.9909 - val_scaled_adversarial_loss: 0.0555\n",
      "Epoch 959/1000\n",
      "12/12 [==============================] - 6s 517ms/step - loss: 0.0901 - sparse_categorical_crossentropy: 0.0202 - sparse_categorical_accuracy: 0.9925 - scaled_adversarial_loss: 0.0699 - val_loss: 0.0781 - val_sparse_categorical_crossentropy: 0.0414 - val_sparse_categorical_accuracy: 0.9881 - val_scaled_adversarial_loss: 0.0367\n",
      "Epoch 960/1000\n",
      "12/12 [==============================] - 8s 624ms/step - loss: 0.0918 - sparse_categorical_crossentropy: 0.0222 - sparse_categorical_accuracy: 0.9920 - scaled_adversarial_loss: 0.0696 - val_loss: 0.0749 - val_sparse_categorical_crossentropy: 0.0388 - val_sparse_categorical_accuracy: 0.9902 - val_scaled_adversarial_loss: 0.0361\n",
      "Epoch 961/1000\n",
      "12/12 [==============================] - 5s 389ms/step - loss: 0.0962 - sparse_categorical_crossentropy: 0.0247 - sparse_categorical_accuracy: 0.9907 - scaled_adversarial_loss: 0.0715 - val_loss: 0.0905 - val_sparse_categorical_crossentropy: 0.0293 - val_sparse_categorical_accuracy: 0.9909 - val_scaled_adversarial_loss: 0.0612\n",
      "Epoch 962/1000\n",
      "12/12 [==============================] - 5s 392ms/step - loss: 0.0943 - sparse_categorical_crossentropy: 0.0202 - sparse_categorical_accuracy: 0.9934 - scaled_adversarial_loss: 0.0741 - val_loss: 0.0789 - val_sparse_categorical_crossentropy: 0.0300 - val_sparse_categorical_accuracy: 0.9930 - val_scaled_adversarial_loss: 0.0489\n",
      "Epoch 963/1000\n",
      "12/12 [==============================] - 5s 383ms/step - loss: 0.0910 - sparse_categorical_crossentropy: 0.0214 - sparse_categorical_accuracy: 0.9927 - scaled_adversarial_loss: 0.0697 - val_loss: 0.0821 - val_sparse_categorical_crossentropy: 0.0336 - val_sparse_categorical_accuracy: 0.9902 - val_scaled_adversarial_loss: 0.0484\n",
      "Epoch 964/1000\n",
      "12/12 [==============================] - 5s 403ms/step - loss: 0.0913 - sparse_categorical_crossentropy: 0.0215 - sparse_categorical_accuracy: 0.9927 - scaled_adversarial_loss: 0.0697 - val_loss: 0.0835 - val_sparse_categorical_crossentropy: 0.0292 - val_sparse_categorical_accuracy: 0.9909 - val_scaled_adversarial_loss: 0.0543\n",
      "Epoch 965/1000\n",
      "12/12 [==============================] - 5s 394ms/step - loss: 0.0920 - sparse_categorical_crossentropy: 0.0233 - sparse_categorical_accuracy: 0.9923 - scaled_adversarial_loss: 0.0687 - val_loss: 0.0779 - val_sparse_categorical_crossentropy: 0.0293 - val_sparse_categorical_accuracy: 0.9916 - val_scaled_adversarial_loss: 0.0486\n",
      "Epoch 966/1000\n",
      "12/12 [==============================] - 5s 401ms/step - loss: 0.0998 - sparse_categorical_crossentropy: 0.0231 - sparse_categorical_accuracy: 0.9920 - scaled_adversarial_loss: 0.0767 - val_loss: 0.0775 - val_sparse_categorical_crossentropy: 0.0325 - val_sparse_categorical_accuracy: 0.9881 - val_scaled_adversarial_loss: 0.0450\n",
      "Epoch 967/1000\n",
      "12/12 [==============================] - 5s 439ms/step - loss: 0.0943 - sparse_categorical_crossentropy: 0.0252 - sparse_categorical_accuracy: 0.9914 - scaled_adversarial_loss: 0.0691 - val_loss: 0.0763 - val_sparse_categorical_crossentropy: 0.0308 - val_sparse_categorical_accuracy: 0.9902 - val_scaled_adversarial_loss: 0.0455\n",
      "Epoch 968/1000\n",
      "12/12 [==============================] - 6s 473ms/step - loss: 0.0934 - sparse_categorical_crossentropy: 0.0259 - sparse_categorical_accuracy: 0.9897 - scaled_adversarial_loss: 0.0675 - val_loss: 0.0796 - val_sparse_categorical_crossentropy: 0.0318 - val_sparse_categorical_accuracy: 0.9902 - val_scaled_adversarial_loss: 0.0478\n",
      "Epoch 969/1000\n",
      "12/12 [==============================] - 6s 469ms/step - loss: 0.1024 - sparse_categorical_crossentropy: 0.0306 - sparse_categorical_accuracy: 0.9900 - scaled_adversarial_loss: 0.0719 - val_loss: 0.0722 - val_sparse_categorical_crossentropy: 0.0355 - val_sparse_categorical_accuracy: 0.9895 - val_scaled_adversarial_loss: 0.0366\n",
      "Epoch 970/1000\n",
      "12/12 [==============================] - 6s 458ms/step - loss: 0.0978 - sparse_categorical_crossentropy: 0.0259 - sparse_categorical_accuracy: 0.9897 - scaled_adversarial_loss: 0.0719 - val_loss: 0.0921 - val_sparse_categorical_crossentropy: 0.0379 - val_sparse_categorical_accuracy: 0.9895 - val_scaled_adversarial_loss: 0.0542\n",
      "Epoch 971/1000\n",
      "12/12 [==============================] - 6s 477ms/step - loss: 0.0906 - sparse_categorical_crossentropy: 0.0197 - sparse_categorical_accuracy: 0.9941 - scaled_adversarial_loss: 0.0710 - val_loss: 0.0829 - val_sparse_categorical_crossentropy: 0.0373 - val_sparse_categorical_accuracy: 0.9895 - val_scaled_adversarial_loss: 0.0456\n",
      "Epoch 972/1000\n",
      "12/12 [==============================] - 6s 472ms/step - loss: 0.0985 - sparse_categorical_crossentropy: 0.0286 - sparse_categorical_accuracy: 0.9920 - scaled_adversarial_loss: 0.0699 - val_loss: 0.0818 - val_sparse_categorical_crossentropy: 0.0327 - val_sparse_categorical_accuracy: 0.9930 - val_scaled_adversarial_loss: 0.0492\n",
      "Epoch 973/1000\n",
      "12/12 [==============================] - 6s 474ms/step - loss: 0.0992 - sparse_categorical_crossentropy: 0.0282 - sparse_categorical_accuracy: 0.9893 - scaled_adversarial_loss: 0.0710 - val_loss: 0.0836 - val_sparse_categorical_crossentropy: 0.0303 - val_sparse_categorical_accuracy: 0.9916 - val_scaled_adversarial_loss: 0.0534\n",
      "Epoch 974/1000\n",
      "12/12 [==============================] - 6s 480ms/step - loss: 0.0907 - sparse_categorical_crossentropy: 0.0204 - sparse_categorical_accuracy: 0.9941 - scaled_adversarial_loss: 0.0703 - val_loss: 0.0888 - val_sparse_categorical_crossentropy: 0.0386 - val_sparse_categorical_accuracy: 0.9881 - val_scaled_adversarial_loss: 0.0502\n",
      "Epoch 975/1000\n",
      "12/12 [==============================] - 6s 472ms/step - loss: 0.0992 - sparse_categorical_crossentropy: 0.0260 - sparse_categorical_accuracy: 0.9921 - scaled_adversarial_loss: 0.0732 - val_loss: 0.1106 - val_sparse_categorical_crossentropy: 0.0372 - val_sparse_categorical_accuracy: 0.9902 - val_scaled_adversarial_loss: 0.0734\n",
      "Epoch 976/1000\n",
      "12/12 [==============================] - 6s 493ms/step - loss: 0.0980 - sparse_categorical_crossentropy: 0.0273 - sparse_categorical_accuracy: 0.9904 - scaled_adversarial_loss: 0.0707 - val_loss: 0.0761 - val_sparse_categorical_crossentropy: 0.0392 - val_sparse_categorical_accuracy: 0.9895 - val_scaled_adversarial_loss: 0.0369\n",
      "Epoch 977/1000\n",
      "12/12 [==============================] - 6s 482ms/step - loss: 0.1048 - sparse_categorical_crossentropy: 0.0343 - sparse_categorical_accuracy: 0.9883 - scaled_adversarial_loss: 0.0705 - val_loss: 0.0818 - val_sparse_categorical_crossentropy: 0.0443 - val_sparse_categorical_accuracy: 0.9916 - val_scaled_adversarial_loss: 0.0375\n",
      "Epoch 978/1000\n",
      "12/12 [==============================] - 5s 449ms/step - loss: 0.0960 - sparse_categorical_crossentropy: 0.0271 - sparse_categorical_accuracy: 0.9911 - scaled_adversarial_loss: 0.0689 - val_loss: 0.0866 - val_sparse_categorical_crossentropy: 0.0361 - val_sparse_categorical_accuracy: 0.9909 - val_scaled_adversarial_loss: 0.0505\n",
      "Epoch 979/1000\n",
      "12/12 [==============================] - 4s 371ms/step - loss: 0.0992 - sparse_categorical_crossentropy: 0.0252 - sparse_categorical_accuracy: 0.9906 - scaled_adversarial_loss: 0.0740 - val_loss: 0.0904 - val_sparse_categorical_crossentropy: 0.0374 - val_sparse_categorical_accuracy: 0.9895 - val_scaled_adversarial_loss: 0.0530\n",
      "Epoch 980/1000\n",
      "12/12 [==============================] - 5s 391ms/step - loss: 0.0955 - sparse_categorical_crossentropy: 0.0250 - sparse_categorical_accuracy: 0.9909 - scaled_adversarial_loss: 0.0706 - val_loss: 0.0863 - val_sparse_categorical_crossentropy: 0.0348 - val_sparse_categorical_accuracy: 0.9895 - val_scaled_adversarial_loss: 0.0515\n",
      "Epoch 981/1000\n",
      "12/12 [==============================] - 5s 406ms/step - loss: 0.1078 - sparse_categorical_crossentropy: 0.0343 - sparse_categorical_accuracy: 0.9893 - scaled_adversarial_loss: 0.0735 - val_loss: 0.0869 - val_sparse_categorical_crossentropy: 0.0332 - val_sparse_categorical_accuracy: 0.9923 - val_scaled_adversarial_loss: 0.0537\n",
      "Epoch 982/1000\n",
      "12/12 [==============================] - 5s 379ms/step - loss: 0.1089 - sparse_categorical_crossentropy: 0.0338 - sparse_categorical_accuracy: 0.9883 - scaled_adversarial_loss: 0.0751 - val_loss: 0.0865 - val_sparse_categorical_crossentropy: 0.0403 - val_sparse_categorical_accuracy: 0.9895 - val_scaled_adversarial_loss: 0.0462\n",
      "Epoch 983/1000\n",
      "12/12 [==============================] - 4s 374ms/step - loss: 0.1042 - sparse_categorical_crossentropy: 0.0321 - sparse_categorical_accuracy: 0.9872 - scaled_adversarial_loss: 0.0721 - val_loss: 0.0851 - val_sparse_categorical_crossentropy: 0.0383 - val_sparse_categorical_accuracy: 0.9909 - val_scaled_adversarial_loss: 0.0469\n",
      "Epoch 984/1000\n",
      "12/12 [==============================] - 5s 388ms/step - loss: 0.1016 - sparse_categorical_crossentropy: 0.0309 - sparse_categorical_accuracy: 0.9909 - scaled_adversarial_loss: 0.0707 - val_loss: 0.0738 - val_sparse_categorical_crossentropy: 0.0271 - val_sparse_categorical_accuracy: 0.9909 - val_scaled_adversarial_loss: 0.0467\n",
      "Epoch 985/1000\n",
      "12/12 [==============================] - 5s 381ms/step - loss: 0.1015 - sparse_categorical_crossentropy: 0.0268 - sparse_categorical_accuracy: 0.9913 - scaled_adversarial_loss: 0.0747 - val_loss: 0.0806 - val_sparse_categorical_crossentropy: 0.0290 - val_sparse_categorical_accuracy: 0.9909 - val_scaled_adversarial_loss: 0.0516\n",
      "Epoch 986/1000\n",
      "12/12 [==============================] - 5s 388ms/step - loss: 0.0955 - sparse_categorical_crossentropy: 0.0263 - sparse_categorical_accuracy: 0.9909 - scaled_adversarial_loss: 0.0693 - val_loss: 0.0851 - val_sparse_categorical_crossentropy: 0.0354 - val_sparse_categorical_accuracy: 0.9902 - val_scaled_adversarial_loss: 0.0497\n",
      "Epoch 987/1000\n",
      "12/12 [==============================] - 5s 378ms/step - loss: 0.1027 - sparse_categorical_crossentropy: 0.0292 - sparse_categorical_accuracy: 0.9906 - scaled_adversarial_loss: 0.0735 - val_loss: 0.0791 - val_sparse_categorical_crossentropy: 0.0310 - val_sparse_categorical_accuracy: 0.9909 - val_scaled_adversarial_loss: 0.0481\n",
      "Epoch 988/1000\n",
      "12/12 [==============================] - 5s 376ms/step - loss: 0.0928 - sparse_categorical_crossentropy: 0.0242 - sparse_categorical_accuracy: 0.9920 - scaled_adversarial_loss: 0.0686 - val_loss: 0.0685 - val_sparse_categorical_crossentropy: 0.0314 - val_sparse_categorical_accuracy: 0.9930 - val_scaled_adversarial_loss: 0.0371\n",
      "Epoch 989/1000\n",
      "12/12 [==============================] - 5s 387ms/step - loss: 0.0910 - sparse_categorical_crossentropy: 0.0208 - sparse_categorical_accuracy: 0.9921 - scaled_adversarial_loss: 0.0702 - val_loss: 0.0770 - val_sparse_categorical_crossentropy: 0.0330 - val_sparse_categorical_accuracy: 0.9895 - val_scaled_adversarial_loss: 0.0440\n",
      "Epoch 990/1000\n",
      "12/12 [==============================] - 5s 378ms/step - loss: 0.0906 - sparse_categorical_crossentropy: 0.0203 - sparse_categorical_accuracy: 0.9937 - scaled_adversarial_loss: 0.0703 - val_loss: 0.0746 - val_sparse_categorical_crossentropy: 0.0304 - val_sparse_categorical_accuracy: 0.9923 - val_scaled_adversarial_loss: 0.0442\n",
      "Epoch 991/1000\n",
      "12/12 [==============================] - 5s 383ms/step - loss: 0.0927 - sparse_categorical_crossentropy: 0.0237 - sparse_categorical_accuracy: 0.9909 - scaled_adversarial_loss: 0.0690 - val_loss: 0.0812 - val_sparse_categorical_crossentropy: 0.0316 - val_sparse_categorical_accuracy: 0.9895 - val_scaled_adversarial_loss: 0.0496\n",
      "Epoch 992/1000\n",
      "12/12 [==============================] - 5s 380ms/step - loss: 0.0988 - sparse_categorical_crossentropy: 0.0262 - sparse_categorical_accuracy: 0.9911 - scaled_adversarial_loss: 0.0726 - val_loss: 0.0950 - val_sparse_categorical_crossentropy: 0.0422 - val_sparse_categorical_accuracy: 0.9874 - val_scaled_adversarial_loss: 0.0528\n",
      "Epoch 993/1000\n",
      "12/12 [==============================] - 5s 382ms/step - loss: 0.1006 - sparse_categorical_crossentropy: 0.0303 - sparse_categorical_accuracy: 0.9918 - scaled_adversarial_loss: 0.0703 - val_loss: 0.0859 - val_sparse_categorical_crossentropy: 0.0373 - val_sparse_categorical_accuracy: 0.9895 - val_scaled_adversarial_loss: 0.0486\n",
      "Epoch 994/1000\n",
      "12/12 [==============================] - 5s 389ms/step - loss: 0.1101 - sparse_categorical_crossentropy: 0.0345 - sparse_categorical_accuracy: 0.9890 - scaled_adversarial_loss: 0.0756 - val_loss: 0.0762 - val_sparse_categorical_crossentropy: 0.0290 - val_sparse_categorical_accuracy: 0.9909 - val_scaled_adversarial_loss: 0.0472\n",
      "Epoch 995/1000\n",
      "12/12 [==============================] - 5s 378ms/step - loss: 0.1016 - sparse_categorical_crossentropy: 0.0319 - sparse_categorical_accuracy: 0.9895 - scaled_adversarial_loss: 0.0696 - val_loss: 0.0882 - val_sparse_categorical_crossentropy: 0.0419 - val_sparse_categorical_accuracy: 0.9902 - val_scaled_adversarial_loss: 0.0462\n",
      "Epoch 996/1000\n",
      "12/12 [==============================] - 5s 388ms/step - loss: 0.1069 - sparse_categorical_crossentropy: 0.0351 - sparse_categorical_accuracy: 0.9883 - scaled_adversarial_loss: 0.0718 - val_loss: 0.0917 - val_sparse_categorical_crossentropy: 0.0428 - val_sparse_categorical_accuracy: 0.9902 - val_scaled_adversarial_loss: 0.0489\n",
      "Epoch 997/1000\n",
      "12/12 [==============================] - 4s 376ms/step - loss: 0.0979 - sparse_categorical_crossentropy: 0.0229 - sparse_categorical_accuracy: 0.9923 - scaled_adversarial_loss: 0.0750 - val_loss: 0.1172 - val_sparse_categorical_crossentropy: 0.0395 - val_sparse_categorical_accuracy: 0.9888 - val_scaled_adversarial_loss: 0.0777\n",
      "Epoch 998/1000\n",
      "12/12 [==============================] - 5s 379ms/step - loss: 0.1083 - sparse_categorical_crossentropy: 0.0337 - sparse_categorical_accuracy: 0.9886 - scaled_adversarial_loss: 0.0746 - val_loss: 0.0887 - val_sparse_categorical_crossentropy: 0.0358 - val_sparse_categorical_accuracy: 0.9916 - val_scaled_adversarial_loss: 0.0529\n",
      "Epoch 999/1000\n",
      "12/12 [==============================] - 5s 390ms/step - loss: 0.0964 - sparse_categorical_crossentropy: 0.0271 - sparse_categorical_accuracy: 0.9900 - scaled_adversarial_loss: 0.0693 - val_loss: 0.0849 - val_sparse_categorical_crossentropy: 0.0327 - val_sparse_categorical_accuracy: 0.9902 - val_scaled_adversarial_loss: 0.0523\n",
      "Epoch 1000/1000\n",
      "12/12 [==============================] - 5s 388ms/step - loss: 0.0915 - sparse_categorical_crossentropy: 0.0209 - sparse_categorical_accuracy: 0.9930 - scaled_adversarial_loss: 0.0706 - val_loss: 0.0801 - val_sparse_categorical_crossentropy: 0.0342 - val_sparse_categorical_accuracy: 0.9902 - val_scaled_adversarial_loss: 0.0460\n"
     ]
    },
    {
     "data": {
      "text/plain": "<keras.callbacks.History at 0x254cfbf39d0>"
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "adv_model.fit({'feature': X_train, 'label': y_train}, epochs=1000, batch_size=512, validation_data={'feature': X_test, 'label': y_test})"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {
    "id": "Pmt7mlJoQ-Np",
    "pycharm": {
     "name": "#%%\n"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "1430/1430 [==============================] - 12s 9ms/step - loss: 0.0810 - sparse_categorical_crossentropy: 0.0326 - sparse_categorical_accuracy: 0.9902 - scaled_adversarial_loss: 0.0484\n"
     ]
    },
    {
     "data": {
      "text/plain": "[0.08104975521564484,\n 0.032616693526506424,\n 0.9902098178863525,\n 0.048432864248752594]"
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "adv_model.evaluate({'feature': X_test, 'label': y_test}, batch_size=1)"
   ]
  }
 ],
 "metadata": {
  "colab": {
   "provenance": [],
   "mount_file_id": "1l_2YpamsRqa2kvQbF6VcRh1L-ZVNw2LN",
   "authorship_tag": "ABX9TyOZ6tqQxYPy3g7WnP4d6Wrs"
  },
  "kernelspec": {
   "display_name": "Python 3",
   "name": "python3"
  },
  "language_info": {
   "name": "python"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 0
}